CN114021817A - Optimization decision system for airplane and passenger integrated interference recovery based on situation response - Google Patents

Abstract

The invention belongs to the technical field of optimization decision based on scenario response, and particularly relates to an optimization decision system for airplane and passenger integrated interference recovery based on scenario response. The method comprises the steps of generating a corresponding recovery scheme in advance aiming at the interference situation frequently suffered by an airline company in the past, and storing the recovery scheme into a situation-scheme library; when an airline company suffers from the existing interference situation, matching the interference situation with elements in a situation-scheme library, if highly similar elements exist, extracting a scheme corresponding to the elements, and adjusting through a heuristic algorithm to obtain a final recovery scheme; and if not, accurately solving by establishing an operation research model, and storing the operation research model into a scenario-scheme library. The method can assist the airline companies to rapidly make flight recovery plans, and reduce the loss of the airline companies and passengers. Compared with the traditional recovery method, the method can further improve the solving efficiency and quickly obtain the high-quality airplane and passenger integrated recovery scheme.

Description

Optimization decision system for airplane and passenger integrated interference recovery based on situation response

Technical Field

The invention belongs to the technical field of optimization decision based on scenario response, and particularly relates to an optimization decision system for airplane and passenger integrated interference recovery based on scenario response.

Background

With the continuous development of the economy of China and the improvement of the living standard of people, the demand of people on civil aviation trip is continuously increased, and the air transportation industry also enters a rapid development period. According to data published in the Chinese civil aviation newspaper, the national civil aviation fleet reaches 6747 frames, 39 million-level airports in the country reach 39, and the total transportation scale is stable in the second world as early as 2021. However, due to the existence of numerous adverse factors such as frequent extreme weather and large organization size in recent years, airlines are often affected by various interference events, so that a large number of flights are delayed or cancelled, and huge economic losses are brought to both the airlines and passengers. Therefore, how to rapidly make a high-quality recovery scheme when an airport, an airplane or a flight is disturbed, and reducing the passenger residence time and the number of flight cancellations for an airline company becomes a key ring in the operation management of the airline company.

In the early days of recovery of disturbed flights and passengers, many airlines were manually programmed by personnel associated with the AOCC (operations control center) to reformulate new recovery solutions. Generally speaking, a worker determines a related flight interfered with the interference situation according to the interference situation, then reformulates a new flight plan through measures such as flight delayed takeoff, airplane route exchange and flight cancellation, and then determines the routing of an interfered passenger according to the new flight plan. Although this recovery method can reduce the loss of the airline to some extent, it usually takes a long time and the recovery scheme is of low quality, and is slowly abandoned by the airline. Later, with the wide application of business operational research software and heuristic algorithms in the field of enterprise operation management, in recent years, some airlines have started to use relevant decision-making assisting software to help the airlines to make recovery plans after interference, but more of the software helps the airlines to make real-time decisions, that is, relevant personnel input flight and passenger related data and interference scenarios, and the software is solved through internally set algorithms. Although the solution speed and the quality of the recovery scheme are improved remarkably compared with the traditional manual arrangement, when the interference scale and the number of flights are large, the solution efficiency of the related software is still not high, and the practical requirements of an airline company cannot be met sometimes. Therefore, a faster solution is needed to assist the airline in making interference recovery decisions.

At present, many related patent applications and academic journal papers about flight disturbance recovery can be found through published data. Among them, patent aspects include "decision support system, method and storage medium for abnormal flight recovery" under publication No. CN113139703A, and "risk management-based regional multiple airport abnormal flight recovery method" under publication No. CN 112862258A. In academic journals, how to make matters and the like in journal "journal of university of aerospace, Beijing" journal of aviation and space "published a paper" abnormal flight recovery technology based on effective transit time prediction ", and in journal" science technology and engineering "published a paper of omnibus and the like in Yang Xin" published an integrated recovery of disturbed flights of an airline company under cruise speed control ". Although the above patent and published paper respectively design different recovery methods for the auxiliary airline under different conditions and perspectives, there are some disadvantages, for example, the setting of the interference scenario is too simple from the content point of view, and the serious influence of the complex interference scenario on the airline is not considered. The algorithm efficiency and the solution efficiency are not high, and the practical requirements of large-scale airlines with hundreds of airplanes cannot be met.

Disclosure of Invention

The invention aims to provide an optimization decision system for airplane and passenger integrated interference recovery based on situation response.

An optimization decision system for airplane and passenger integrated interference recovery based on scenario response comprises a scenario-scheme library construction module, a scenario matching module, a scenario response module and a scenario evaluation module;

the scene-scheme library construction module is used for constructing past and predicted interference scenes possibly suffered by an airline company in the future and a recovery scheme corresponding to the interference scenes to generate a scene-scheme library SP; each element in the scenario-solution library SP is an SP_i＝(l_i,s_i,p_i)；l_iA tag indicating a type of interference; s_iRepresenting the attributes of the interference recovery object, specifically comprising the number flt _ size of the fleet to be recovered and the travel plan iti _ size of the related passengers; p is a radical of_iThen the corresponding recovery scheme is indicated;

the scenario matching module is used for the scenario SP when the airline company suffers from the existing interference_now＝(l_now,s_now) Upon impact, label l according to interference type_nowAnd interference recovery object attribute s_nowRapidly matching with elements in a scene-scheme library SP, and judging whether highly similar elements exist or not;

the situation coping module is used for acquiring a recovery scheme corresponding to the interference situation suffered by the airline company according to the interference situation; if the situation matching module judges that the situation SP exists in the pre-generated situation-scheme library SP and interferes with the situation SP_now＝(l_now,s_now) Highly similar elements SP_jThen the scenario reply module adjusts SP_jRecovery scheme p in (1)_jTo acquire the data corresponding to the interference scenario SP_nowOf the final recovery scheme p_now(ii) a If the elements with the similar height are not matched, the scene response module carries out real-time response operation, and an airplane and passenger integrated interference recovery model is established to solve an optimal recovery scheme;

the scene evaluation module is used for updating and maintaining the scene-scheme library SP.

Further, the method for generating the scenario-scenario library SP in the scenario-scenario library construction module specifically includes:

step 1.1: setting interference type label l_i；

The interference type labels are divided into three types, namely airport interference ED, airplane interference AD and flight interference FD; interference situations common to airlines can be represented by an interference type label l ═ { ED, AD, FD }; when there is no interference of a certain type, setting it as an empty set phi;

wherein airport interference is represented by the symbols ED { (AR), (TW), (L) }; AR represents airport sequence number; TW represents an interference time window; l represents the capacity loss proportion of the takeoff or landing runway of the airport, when L is 1, the airport is completely closed, and any airplane is not allowed to take off and land;

the airplane disturbance is represented by the symbols AD { (AC), (TW) }, AC represents the airplane serial number; TW represents a time window in which the aircraft is disturbed;

flight interference is represented by symbols FD { (f), (DT) }, where f represents the interfered flight number; DT represents the type of disturbance, including both delayed flight takeoff D or cancellation C;

step 1.2: determining an interference recovery object attribute s_i；

Let DS (l)_now) Representing an interfered scenario l_nowInfluence is related to the size of the fleet, and flt _ size is determined_nowAt least, flt _ size should be satisfied_now≥DS(l_now) To ensure that all interfered flights are taken into account; with flt _ size, considering that different fleets are allowed to interchange lanes under certain conditions_nowThe original cancelled flight may be executed by an airplane of another model and is not cancelled finally, so that a better recovery scheme is obtained, but at the same time, the recovery difficulty is increased sharply, so that the recovery scheme cannot be obtained in a short time, and therefore, under the framework, the recovery object attribute s is interfered_iIs determined when flt _ size ≧ DS (l)_now) Is a hyper-parameter and needs to be carried out by aviationCompany fixed;

step 1.3: determining an interference recovery scheme p_i。

Further, in the scenario-scenario library construction module, based on the scenario-scenario library SP being completely created, in order to accelerate the existing interference scenario SP_nowAnd respectively setting 3 sub-libraries for the SP libraries at the speed of subsequent matching with the scenario scheme library SP, wherein the first sub-library sorts all elements in the SP by airport sequence numbers according to airport interference, the second sub-library sorts all elements in the SP by airport sequence numbers according to airplane sequence numbers, and the third sub-library sorts all elements according to flight sequence numbers.

Further, the scene matching module labels l according to interference types_nowAnd interference recovery object attribute s_nowThe method for rapidly matching with the elements in the scenario-scenario library SP and judging whether highly similar elements exist specifically comprises the following steps:

step 2.1: defining a matching degree formula;

defining an inner matching formula and an outer matching formula, the inner matching formula being used for pair s_nowMatching is performed, defined as:

if and only if s_now＝＝s_jWhen the sizes of the fleets related to the recovery object are the same, the internal matching degree is 1;

in terms of the external matching formula, according to l_nowThere are three different interference scenarios, and different similarity formulas are defined respectively:

A. airport interference similarity formula:

B. airplane interference similarity formula:

C. flight interference similarity formula:

D. the outer matching similarity formula:

formula A is a matching degree formula of airport interference, wherein a belongs to SP_now(ED) denotes extraction of SP_nowRelated elements of (1) about airport interference scenarios; | a | represents the number of flights directly affected by airport interference; [ start ]_a,end_a]An interference time window representing an existing airport interference scenario; [ start ]_b,end_b]Then represents the interference time window of the matched element; if the two interference time windows are identical, then

lq_aRepresenting an airport capacity loss value; if (a ═ b) indicates whether or not the airport is the same;

the formula B is a matching degree formula of the airplane interference, wherein | | | c | | | represents the number of flights directly affected by the airport interference; if (c) represents whether the aircraft is the same airplane or not;

formula C is a flight interference matching degree formula, where del (f) represents the delay time of flight f; the is _ same (f, h) function represents that whether the two flights are consistent or not is judged, if so, the value is 1, otherwise, the value is 0;

denominator | | SP in formula D_nowI represents the number of all flights directly affected by the existing interference scenario, and the numerator is the sum of the matching values of the three interference scenarios; the definition of the formula A, B, C can ensure that the O _ match (SP)_now,SP_j)∈[0,1]；

Step 2.2: defining a matching algorithm;

according to the existing interference scenario SP_nowRespectively calculating the flight number influenced by the ED, AD and FD, respectively marking as | | a | |, | c |, and | | | f |, and calculating the corresponding weight w_||a||、w_||b||、w_||c||：

If w is_||a||Relative to w_||b||、w_||c||If larger, then SP will be_nowThe elements of the middle ED and the first sub-library are firstly subjected to interference similarity function P according to the airport_ED(SP_now,SP_j) Calculating, and taking the object with the top rank as a candidate object; then the SP is put again_nowThe AD element in (1) and the candidate object carry out an airplane interference similarity function P_AD(SP_now,SP_j) Calculating, selecting the top-ranked as new candidate, and selecting SP_nowFD element of (1) and new candidate object carry out flight interference similarity function P_FD(SP_now,SP_j) Calculating, and selecting the object with the top rank as a final candidate object; finally, an external matching formula O _ match (SP) is applied_now,SP_j) The final candidate is compared with the SP_nowPerforming matching calculation, and determining whether highly similar element SP exists according to the size of the first-ranked matching value_j；

If w is_||a||、w_||b||、w_||c||If the numerical values of the three are not very different, respectively using the parallel computing method to calculate the SP_nowThe ED element in the first sub-library is matched with the first sub-library, the AD element is matched with the second sub-library, and the FD element is matched with the third sub-library; collecting the intersection of the three candidate sets generated respectively to observe whether the intersection is empty; if the result is null, indicating that no object which is highly matched with the SP library exists; otherwise, applying an external matching formula O _ match (SP)_now,SP_j) The intersection element is compared with the SP_nowPerforming matching calculation, calculating a total matching value, and determining whether highly similar elements SP exist according to the size of the first-ranked matching value_j。

Further, in the scenario response module, if the highly similar elements are not matched, the scenario response module performs real-time response operation, and the method for establishing the airplane and passenger integrated interference recovery model to solve the optimal recovery scheme specifically includes:

step 3.1: constructing an original flight arc and a delayed flight arc for each flight by applying a time-space network technology according to an original flight plan of an airline company;

step 3.2: according to interference scenarios SP_now＝(l_now,s_now) Determining a flight arc set directly affected with the flight network generated in the step 3.1, and recording the flight arc set as df; substituting the Df and related parameters of the original flight plan into a pure aircraft flow network model for solving to obtain all flight sets influenced by a ripple effect of a flight network, and recording the flight sets as Df; determining the interfered passenger travel sets related to the Df according to the Df, and respectively generating route sets which can be changed and are marked as Tl for the travel sets according to the flight network generated in the step 3.1, the shortest connection time required by two adjacent flights and the condition that the airports are the same;

step 3.3: on the basis of obtaining Df, Tl and parameters related to flights and passengers, an airplane and passenger integrated interference recovery model is constructed, and a recovery scheme is solved; if the interfered flight set in the recovery scheme is consistent with the Df, the solution is completed, and the scheme is a final recovery scheme; otherwise, returning to step 3.2, the route set which can be re-signed is re-arranged for disturbed passenger trips not considered before.

Further, in the scenario correspondence module, if highly similar elements are matched, a heuristic adjustment algorithm is adopted, and SP is adjusted_jRecovery scheme p in (1)_jTo acquire the data corresponding to the interference scenario SP_nowOf the final recovery scheme p_now；

Step 4.1: according to interference labels l_jAnd l_nowAnd an object to be restored s_jAnd s_nowIs applied to the initial interference recovery scheme p_jPerforming preliminary adjustment;

step 4.1.1: find out l_jIn a particular interference scenario, by symbols

Is represented by_nowAnd l_jSame interference scenario between, ld_j＝l_j-l_commonIs represented by_jThe flight recovery method comprises the following steps of (1) adjusting all flights involved in the special interference scenarios according to an original flight recovery plan;

step 4.1.2: finding s_jAccording to s_nowMaking an adjustment by a symbol

Denotes s_nowAnd s_jSame moiety between, sd_j＝s_j-s_nowDenotes s_jA specific interference scenario; to s_jIs present but s_nowRemoving the missing passenger journey according to s_nowNumber of passengers in each journey p_jUpdating the corresponding number of passengers; record the obtained initial adjustment recovery scheme as

Step 4.2: determining an interference recovery range, including a flight interference recovery limit range and a passenger journey recovery limit range; since the initial adjustment recovery scheme is already available

Therefore, the final recovery scheme p is obtained by adopting a local optimization mode without optimizing all flights and passenger trips_now；

First according to_nowInterference scenario ld specific to_now＝l_now-l_commonDetermining affected flight sets, then determining related aircraft sets from the flight sets, extracting flight strings executed by the aircraft on the current day as flight interference recovery limit range, and recordingIs U_f(ii) a Determining the passenger journey recovery limit range according to the journeys contained in the range limited by the flight interference recovery, and recording the range as U_I；

Step 4.3: acquiring a final recovery scheme;

step 4.3.1: restoring a schema from preliminary adjustment

Middle eliminating U_fAnd U_IIs marked as

Is U_fEstablishing a spatio-temporal network model for all flights in the set as U_IThe passenger itineraries contained in the set are arranged and the route can be changed;

step 4.3.2: solving by applying airplane and passenger integrated interference recovery model in real-time response operation to obtain flight recovery scheme SU_fAnd traveler's trip recovery SU_I；

Step 4.3.3: to SU_I、SU_fAnd

merging is carried out

Get the final recovery scheme p_now。

Further, the method for updating and maintaining the scenario-scenario database SP in the scenario evaluation module specifically includes:

if in the scene matching module, SP_now＝(l_now,s_now) If there is no highly similar element after matching with the scenario-scenario library SP, the recovery scenario p obtained in the scenario response module is recovered_nowTogether, adding the two into a scenario-scheme library SP;

if in the scene matching module, SP_now＝(l_now,s_now) Highly similar elements exist after matching with the scenario-scenario library SP; then the following steps are performed:

step 5.1: for height similarityInterval [ K ]₁,1]Is divided into two subintervals, respectively being [ K₁,K₂]、[K₁,1]；

Step 5.2: obtaining the elements in the scene-scheme library SP and SP calculated by the scene matching module_nowRespectively fall within the interval [ K ]₁,K₂]And [ K ]₁,1]The number of (2) is respectively denoted as N₁,N₂；

Step 5.3: let N be equal to N₁+N₂，NK₂The maximum number of fields with high matching degree; if N is present₂≥NK₂Then do not consider its inclusion in the scenario solution library; if N is present₂＜NK₂A random number is generated, accepted with a probability of epsilon,

δ is a scale control influence factor, and the larger the value thereof, the smaller the overall scale of the scenario-scenario library SP.

The invention has the beneficial effects that:

the system comprises a scene-scheme library construction module, a scene matching module, a scene coping module and a scene evaluation module. Generating a corresponding recovery scheme in advance aiming at the interference situation frequently suffered by an airline company in the past, and storing the recovery scheme into a situation-scheme library; when an airline company suffers from the existing interference situation, matching the interference situation with elements in a situation-scheme library, if highly similar elements exist, extracting a scheme corresponding to the elements, and adjusting through a heuristic algorithm to obtain a final recovery scheme; and if not, accurately solving by establishing an operation research model, and storing the operation research model into a scenario-scheme library. Compared with the traditional recovery method, the method can further improve the solving efficiency, quickly obtain the high-quality airplane and passenger integrated recovery scheme, and meet the practical requirements of the airline company. The method can assist the airline companies to rapidly make flight recovery plans, and reduce the loss of the airline companies and passengers.

Drawings

FIG. 1 is a framework flow diagram of the present invention.

FIG. 2 is a drawing of_jAnd l_nowCo-interference scenario and characteristic interference scenario schematics

Fig. 3 is a schematic diagram of a range of limit of flight interference recovery in a heuristic adjustment algorithm of the invention.

Detailed Description

The invention is further described below with reference to the accompanying drawings.

The invention discloses an optimization decision system for airplane and passenger integrated interference recovery based on scenario response, which can assist an airline company to make a flight recovery plan quickly and reduce the loss of the airline company and passengers. The system comprises a scene-scheme library construction module, a scene matching module, a scene coping module and a scene evaluation module. Generating a corresponding recovery scheme in advance aiming at the interference situation frequently suffered by an airline company in the past, and storing the recovery scheme into a situation-scheme library; when an airline company suffers from the existing interference situation, matching the interference situation with elements in a situation-scheme library, if highly similar elements exist, extracting a scheme corresponding to the elements, and adjusting through a heuristic algorithm to obtain a final recovery scheme; and if not, accurately solving by establishing an operation research model, and storing the operation research model into a scenario-scheme library. Compared with the traditional recovery method, the method can further improve the solving efficiency, quickly obtain the high-quality airplane and passenger integrated recovery scheme, and meet the practical requirements of the airline company.

The invention comprises the following four modules:

s1: and a scene-scheme library construction module. The module is mainly used for constructing interference scenarios which an airline company may suffer in the past and in the future and recovery schemes corresponding to the interference scenarios. Let SP be a library of airline scenarios, each element within it

Then consists of three parts, where_iLabel representing interference type, s_iRepresents the attribute of the disturbance recovery object (specifically including the number of fleets to be recovered (flt _ size) and the travel plan of the relevant passengers (iti _ size)), p_iThen it means the relative relationship with itThe recovery scheme should be applied. l_iAnd s_iThe specific value of (A) can be set by the airline company, and p of the scheme is recovered_iThe acquisition can be solved by constructing a mathematical model and applying commercial software.

S2: and a scene matching module. The main function of this module is to take the existing interference scenario SP suffered by the airline company_now＝(l_now,s_now) Matching with elements in the scenario-scheme library SP, and judging whether the elements exist in the scenario-scheme library SP or not_now＝(l_now,s_now) The presence of highly similar elements. If so, extracting the recovery scheme corresponding to the element, adjusting through the heuristic adjusting algorithm mentioned in S3 to obtain a final recovery scheme, and if not, obtaining the final recovery scheme by using the real-time response operation in S3.

S3: and a scenario response module. The module is mainly responsible for acquiring a recovery scheme corresponding to the interference situation suffered by the airline company. According to the matching process of S2, the existing interference scene SP_now＝(l_now,s_now) The recovery method adopted by the scenario response module is different from whether the elements in the scenario-scheme library SP have highly similar elements. When elements with similar height exist, a heuristic adjusting algorithm is used for adjusting SP_jRecovery scheme p in (1)_jTo obtain a corresponding SP_now＝(l_now,s_now) Of the final recovery scheme p_now(ii) a If the highly similar elements are not matched, an airplane and passenger integrated interference recovery model is established, an iterative solving algorithm is designed, and an optimal recovery scheme is quickly obtained by means of commercial solving software, wherein the solving process is called real-time response operation.

S4: and a scene evaluation module. The module is mainly used for updating and maintaining the scenario-scheme library. As a major innovation of the invention, the establishment of the scenario-scheme library can play a role of 'no rain, silk and muir' in the aspect of airline interference management, and fully embodies the idea of 'changing time by space' on the aspect of quick acquisition of the recovery scheme. For the scenario-scheme library, the diversity and completeness of the scenario-scheme library are critical to the implementation effect of the frameworkAnd (4) acting. In order to increase diversity and completeness while controlling the scale of the scenario-scheme library SP, the scenario evaluation module mainly judges a new element SP_i＝(l_i,s_i,p_i) Whether a scenario-scenario library can be incorporated to maintain the diversity and completeness of the scenario-scenario library.

Further, in the context-scenario library building module, the following steps are specifically performed:

s1.1 interference type tag (l)_i) Is set. In the interference type tag (l)_i) In the setting aspect of the method, relevant data of civil aviation in China in recent years are inquired, and weather, self management of an airline company and air control are three main reasons for causing abnormal flights of the airline company in China. Therefore, there are three main categories above the tag setting of the interference type, which are airport interference (abbreviated as ED), airplane interference (AD), and flight interference (FD). The airport interference is represented by symbols ED { (AR), (TW), (L) }, wherein the symbols represent AR airport serial numbers, TW represents interference time windows, L represents the capacity loss proportion of the takeoff or landing runway of the airport, and when L is equal to 1, the airport is completely closed, and no airplane is allowed to take off or land. The aircraft disturbance is represented by the symbols AD { (AC), (TW) }, where AC denotes the aircraft sequence number and TW denotes the time window in which the aircraft is disturbed. Flight interference is represented by the symbols FD { (f), (DT) }, where f denotes the interfered flight number and DT denotes the interference type, including both delayed flight take-off D and cancellation C. Interference situations common to airlines can be represented by the interference type label l ═ { ED, AD, FD }. When there is no interference of a certain type, it can be set to the empty set phi.

S1.2 interference recovery object Attribute (S)_i) And (4) determining. Interference recovery object s_iThe size of the fleet (flt _ size) and the corresponding journey size of the passenger (iti _ size) are mainly involved. Let DS (l)_now) Representing an interfered scenario l_nowInfluence is related to the fleet size, then flt _ size is determined_nowAt least, flt _ size should be satisfied_now≥DS(l_now) It is guaranteed that all interfered flights are taken into account. Of course, different fleets are consideredUnder certain conditions, allows lanes to be interchanged, so as to follow flt _ size_nowThe originally cancelled flights are possibly executed by airplanes of other models and are not cancelled finally, so that a better recovery scheme is obtained, but the recovery difficulty is increased sharply at the same time, so that the recovery scheme cannot be obtained in a short time. Thus in this framework, the interference restores the object property(s)_i) Is determined when flt _ size ≧ DS (l)_now) The condition (2) is an over-parameter and needs to be seized by an airline company.

S1.3 interference recovery scheme (p)_i) And (4) determining. In determining (l)_now,s_now) In the case of (1), p_nowAre obtained mainly according to the modules S2, S3, which will be explained later.

Based on the establishment of the airline scenario-scenario library SP, in order to accelerate the existing interference scenario SP_nowAnd at the speed of subsequent matching with the scenario solution library SP, the method respectively sets 3 sub-libraries for the SP library, wherein the first sub-library sorts all elements in the SP by airport serial numbers according to airport interference, the second sub-library sorts all elements in the SP by airport serial numbers according to airplane serial numbers, and the third sub-library sorts all elements according to flight serial numbers.

Further, in the above scenario matching module, the following steps are specifically performed:

and S2.1, defining a matching degree formula. To be able to adapt the existing interference scenario SP_now＝(l_now,s_now) Matching with the scenario-scheme library SP, an inner matching formula and an outer matching formula are defined. Wherein the internal matching formula is mainly used for s_nowAnd (6) matching. It is defined as:

if and only if s_now＝＝s_jWhen the sizes of the fleet involved in the recovery object are the same, the internal matching degree is 1.

In terms of the external matching formula, then according to l_nowMemory storageIn three different interference scenarios, different similarity formulas are defined respectively:

A. airport interference similarity formula:

B. airplane interference similarity formula:

C. flight interference similarity formula:

D. the outer matching similarity formula:

in the above formula SP_nowRepresenting an interference scenario that the airline is facing, comprising (l)_now,s_now) Two parts, SP_jThen the ith element in the case-schema library is represented, which contains (l)_i,s_i,p_i) And (4) three parts. Denominator | | SP in formula D_nowI | represents the number of all flights directly affected by the existing interference scenario, and the numerator is the sum of the matching values of the three interference scenarios. The definition of the formula A, B, C can ensure that the O _ match (SP)_now,SP_j)∈[0,1]. Formula A is a matching degree formula of airport interference, wherein a belongs to SP_now(ED) denotes extraction of SP_nowRelated elements of (e.g.: a ═ ED { (xiaoshi airport), (9:00-10:00), (1) }), | | | a | | | denotes the number of flights directly affected by airport interference, [ start | ], and_a,end_a]interference time window, [ start ], representing an existing airport interference scenario_b,end_b]Then it indicates that it is matched withThe interference time windows of the matching elements are identical, if the two interference time windows are identical, the interference time windows are matched

lq_aAnd (b) judging whether the airport is the same airport or not. Formula B is a matching degree formula of airplane interference, where | | | c | | | represents the number of flights directly affected by airport interference, c ═ d determines whether the same airplane is present, and the rest is similar to formula a. And the formula C is a flight interference matching degree formula, wherein Del (f) represents the delay time of the flight f, the is _ same (f, h) function is used for judging whether the two flights are consistent, if so, the value is 1, otherwise, the value is 0.

In the matching process, the framework provided by the invention is firstly calculated by using an internal matching degree formula, the candidate objects with the same fleet number are selected from a scene-scheme library, and then an external matching formula is used for determining whether highly similar elements SP exist or not_jIf so, extracting the recovery scheme p_jAs an initial recovery scheme for existing interference scenarios.

S2.2 definition of the matching algorithm. Since the scenario-scenario library SP is very large in scale, if it takes a long time to simply traverse the entire scenario-scenario library, it is impossible to quickly make an interference recovery scenario. Therefore, in order to accelerate the matching speed and quickly obtain the matched result, the matching algorithm is operated according to the following steps:

a. according to the existing interference scenario SP_nowRespectively calculating the flight number influenced by the ED, AD and FD, respectively recording as | | a | |, | c |, | | f | |, and then calculating the corresponding weight by the following formula:

and b.w is sorted according to the numerical value. Without setting the sorted order as w_||a||w_||b||w_||c||。

b.1 if w_||a||Relative to w_||b||、w_||c||The size of the composite material is larger,SP_nowAnd (4) calculating the elements of the middle ED and the sub-library 1 according to an airport interference similarity function, and taking the elements which are ranked earlier as candidate objects. Then the SP is put again_nowThe AD element in the method and the candidate object generated in the last step are subjected to airplane interference similarity function calculation, then the AD element is selected as a new candidate object before ranking, the analogy is carried out until a final candidate object is generated, and whether a recovery scheme is extracted to be used as an SP or not is judged according to the size of a matching value at the first ranking_nowThe initial recovery scheme of (1).

b.2 if w_||a||、w_||b||、w_||c||If the numerical values of the three are not very different, respectively using the parallel computing method to calculate the SP_nowThe ED element in (1) is matched with the sub-library 1, the AD element is matched with the sub-library 2, and so on. And (4) taking the intersection of the three candidate sets generated respectively to observe whether the intersection is empty or not. If the result is null, the SP library is indicated that no related high-matching object exists. Otherwise, the intersection element SP_nowAnd performing matching calculation, calculating a total matching value, and judging whether to extract the recovery scheme as an initial recovery scheme according to the size of the first-ranked matching value.

The existing interference situation SP can be quickly known through the two-step matching operation_nowAnd matching the result with the scenario-scheme library SP, and then adopting different recovery methods in the subsequent scenario coping module according to the result to quickly obtain the final recovery scheme.

Further, in the above scenario handling module, the following steps are specifically performed:

and S3.1, responding to operation in real time. When there is no highly similar interference scenario after the scenario matching operation is performed at S2, a real-time response operation is employed to acquire the interference scenario SP corresponding to the existing interference scenario_nowA corresponding recovery scheme. The real-time response operation is specifically described below.

a. And constructing an original flight arc and a delayed flight arc for each flight according to the original flight plan of the airline company by using the traditional space-time network technology.

b. According to interference scenarios SP_now＝(l_now,s_now) With the flight network generated in aThe set of flight arcs directly affected is determined and is not noted as df. Then, Df and the related parameters of the original flight plan are substituted into the pure airplane flow network model for solving, and all flight sets (denoted as Df, generally speaking, Df is greater than or equal to Df) affected by the ripple effect of the flight network are obtained. And then determining the interfered passenger travel sets related to the Df, and generating route sets (denoted as Tl) which can be switched for the travels respectively according to the flight network generated in the step a under the condition that the shortest connection time required by two adjacent flights is met and the airport is the same.

c. On the basis of obtaining Df, Tl and parameters related to flights and passengers, an airplane and passenger integrated interference recovery model is constructed, and a recovery scheme is obtained by using commercial solving software. If the interfered flight set in the recovery scheme is consistent with the Df, the solution is completed, the scheme is the final recovery scheme, if the interfered flight set is inconsistent with the Df, b is returned, the route set which can be changed for the interfered passenger itinerary which is not considered before is rearranged, and in c, an airplane and passenger integrated interference recovery model is used for obtaining the optimal change scheme.

And S3.2, carrying out heuristic adjustment algorithm. After the operation of scene matching at S2, it is found that there is a highly similar element SP in the scene-solution library SP_jIn the invention, a heuristic adjusting algorithm is adopted to adjust p_jTo obtain the final recovery scheme. The heuristic adjustment algorithm is as follows.

a. And (5) performing preliminary adjustment. According to interference labels l_jAnd l_nowAnd an object to be restored s_jAnd s_nowIs applied to the initial interference recovery scheme p_jAnd (6) adjusting. 1) First, find out l_jIn (symbol for the invention) interference scenarios

Is represented by_nowAnd l_jSame interference scenario between, ld_j＝l_j-l_commonIs represented by_jSpecific interference scenarios) and all flights involved in these specific interference scenarios are adjusted according to the original flight recovery plan.E.g. l_jThere are 6 th planes in [9:00-10:00 ]]Failure of normal use but_nowThere is no such interference scenario, so it can be known that AD ═ 6, [9:00-10:00 ═]}∈ld_jP is adjusted at the time of preliminary adjustment_jThe 6 th plane recovery plan is adjusted to the original flight plan of the 6 th plane, and the passenger journey related to the 6 th plane is also updated in response. 2) Finding s_jAccording to s_nowMake adjustments (symbols for the invention)

Denotes s_nowAnd s_jSame moiety between, sd_j＝s_j-s_nowDenotes s_jThe interference scenario specific). For example to s_jIs present but s_nowRemoving the missing passenger journey, and according to s_nowNumber of passengers in each journey p_jThe corresponding number of passengers is updated, and the like. Through the recovery schemes obtained after the operations, the method is recorded as a primary adjustment recovery scheme and used

And (4) performing representation.

b. And determining the interference recovery range. The interference recovery range determination specifically comprises two parts of a flight interference recovery limit range and a passenger journey recovery limit range. Since the initial adjustment recovery scheme is already available

Therefore, the final recovery scheme p is obtained mainly in a local optimization mode without optimizing all flights and passenger trips_now. 1) First according to_nowInterference scenario ld specific to_now＝l_now-l_commonDetermining the affected flight sets, then determining relevant airplane sets from the flight sets, extracting flight strings executed by the airplanes on the same day as a flight interference recovery limit range (marked as U)_f). 2) Determination of limit range for passenger journey recoveryIs determined according to the range of the flight interference recovery limit (marked as U)_I)。

c. And finally, acquiring the recovery scheme. 1) First recover from preliminary adjustments to the scenario

Middle eliminating U_fAnd U_IAnd is recorded as

And is U_fEstablishing a spatio-temporal network model for all flights in the set as U_IThe passenger itineraries contained in the collection are scheduled for a re-sign route. 2) Then, solving is carried out by applying an airplane and passenger integrated interference recovery model in real-time response operation to obtain a flight recovery scheme SU_fAnd passenger trip recovery scheme SU_I. 3) To SU_I、SU_fAnd

merging is carried out

That is, the final recovery scheme p_now。

Further, in the above scenario evaluation module, the following steps are specifically performed:

a. if SP_now＝(l_now,s_now) If there is no high matching condition after matching with the scenario-scenario library, the recovery scenario p obtained in the scenario response module_nowTogether, in the scenario-scenario library, and the three sub-libraries are reordered.

b. If the situation of high matching exists after the situation-scheme library is matched, the following method is adopted for processing:

b1. for high matching interval [ K₁,1]We can divide in advance into two sub-intervals, which are respectively [ K ]₁,K₂]、[K₁,1]。

b2. Calculating elements and SP in the scenario-scheme library according to the scenario matching module_nowCarry out matching ofThe values fall into the interval [ K ]₁,K₂]And [ K ]₁,1]The number of (2) is respectively denoted as N₁,N₂。

b3. Let N be equal to N₁+N₂，NK₂The maximum number of fields with high matching degree. If N is present₂≥NK₂Then the algorithm terminates without regard to its inclusion in the scenario solution library. Otherwise if N is₂＜NK₂Then a random number is randomly generated to accept it with a probability of epsilon, where

δ is a scale control influencing factor, the larger the value, the smaller the overall scale of the SP).

Example 1:

the invention aims to assist an airline company to rapidly make a high-quality recovery scheme aiming at the daily frequent interference situation, and reduce the operation cost of the airline company and the influence of interference events on a travel plan of passengers.

The invention adopts computer technology, and automatically realizes the recovery of interfered airplanes, flights and passenger trips by establishing an optimization model, designing an optimization algorithm and other technical means. As shown in fig. 1, the method includes four modules of scene-scheme library construction, scene matching, scene coping and scene evaluation.

A. The construction of the scenario-scheme library is essentially the process of pre-formulating recovery schemes corresponding to different interference scenarios. Each element therein

Consists of three parts, wherein_iLabel for type of interference, representation s_iDisturbance recovery object attributes (including specifically the number of fleets to be recovered and the travel plan of the relevant passenger), p_iIndicating the recovery scheme corresponding thereto. The subsequent scene matching module essentially judges the existing interference scene SP_now＝(l_now,s_now) And SP_i＝(l_i,s_i) To a similar degree. The main task of the context handling module is to be fastFast acquisition integrated interference recovery scheme p_iThe process of (1). In addition, in order to accelerate the matching process subsequently, in addition to constructing the SP libraries, the invention additionally sets 3 sub-libraries according to the SP libraries, wherein the first sub-library sorts all elements in the SP by airport sequence numbers according to airport interference, the second sub-library sorts all elements in the SP by airport sequence numbers according to airplane sequence numbers, and the third sub-library sorts all elements according to flight sequence numbers.

B. The scene-scheme library matching module mainly comprises two parts: definition of B.1 similarity formula and B.2 matching algorithm

B.1 definition of similarity formula, namely finding the existing interference scene SP from the scene-scheme library SP_now＝(l_now,s_now) Highly similar elements SP_i＝(l_i,s_i). Because of the SP_nowIncludes two parts, so that the recovered object(s) needs to be treated separately_now,s_i) And interference scenarios (l)_now,l_i) A one-to-one match is made. For these two different matches, they are named as inner and outer matches in the present invention.

Wherein the internal match is defined as follows:

if and only if s_now＝＝s_jWhen the sizes of the fleets involved in the recovery object are the same, the internal matching degree is 1, and the rest are 0.

In terms of the external matching formula, different similarity formulas are respectively defined according to three different interference scenarios:

b.1.1 airport interference similarity formula:

b.1.2 aircraft interference similarity formula:

b.1.3 flight interference similarity formula:

b.1.4 external matching similarity formula:

the formula B.1.4 is the total external matching formula, and the formulas B.1.1-B.1.3 are the detailed descriptions of the sub-parts in the formula B.1.4, and the denominator | | | SP_now| represents the scene l subject to the existing interference_nowAll flight numbers directly affected, so the formula B.1.4 can guarantee O _ match (SP)_now,SP_j)∈[0,1]. In the formula b.1.1, considering three parts of contents in airport interference, namely, the number of the interfering airport, the interference time window and the interference degree, the formula b.1.1 is equal to the matching product of the three parts of contents multiplied by the number of flights (i a i) affected by the airport interference. The airplane interference mainly only relates to the number of the interfering airplane and the interference time window, so the formula b.1.2 includes the product of the two parts and then multiplies the number of flights affected by the airplane interference (| c |), and the definition of the formula b.1.3 is similar to the formulas b.1.1 and b.1.2, which is not described herein again.

And B.2, defining a matching algorithm. The matching algorithm is mainly used for solving the problem of how to match a high-quality matching result quickly. Unlike the time-consuming practice of simply matching the entire scenario-solution library SP element on a one-to-one basis. The specific details of the matching algorithm provided by the invention are as follows:

b.2.1 existing interference scenario SP first_nowS in_nowFinding the sum s in the interference scene library SP by using an internal matching formula_nowThe same set of elements, denoted CanSP. The three corresponding sub-libraries are respectively marked as CanSP₁、CanSP₂、CanSP₃

B.2.2 then existing interference scenario SP_nowIn_nowRespectively calculating the flight number influenced by the ED, AD and FD, respectively recording as | | a | |, | c |, | | f | |, and then calculating the corresponding weight by the following formula:

b.2.3 sorting w according to the descending order of the numerical value. Without setting the sorted order as w_||a||≥w_||b||≥w_||c||。

If w is_||a||Not less than 0.6 relative to w_||b||、w_||c||Is larger (meaning w)_||a||+w_||b||Less than or equal to 0.4), then SP_nowThe elements of the ED are firstly compared with the CanSP₁The elements in (1) are calculated according to the airport interference similarity function, and the elements with higher rank are used as candidate objects. Then the SP is put again_nowThe AD element in (1) and the CanSP corresponding to the candidate object generated in the previous step₂The elements in the method are subjected to airplane interference similarity function calculation, then the elements are selected as new candidate objects before ranking, and the steps are analogized in turn and then the SP is used_nowFD element in (1) and CanSP corresponding to the candidate object generated in the previous step₃Until the final candidate object is generated, and judging whether to extract the recovery scheme thereof as the SP according to the size of the first-ranked matching value_nowThe initial recovery scheme of (1).

If w is_||a||、w_||b||、w_||c||The values of the three are not very different, that is, the above condition is not satisfied. Then adopt the parallel computation method to separately make SP_nowED element and CanSP in (1)₁Match AD element with CanSP₂Match FD element with CanSP₃And (6) matching. And (4) taking the intersection of the three candidate sets generated respectively to observe whether the intersection is empty or not. If the result is null, the SP library is indicated that no related high-matching object exists. Otherwise, the intersection element SP_nowPerforming matching calculation, calculating the total matching value, and judging whether to perform matching calculation according to the first ranking matching valueAnd extracting the recovery scheme as the initial recovery scheme.

C. The scene response module mainly comprises two parts: c.1 heuristic adjustment algorithm and C.2 real-time response operation.

According to different matching results obtained from the scene matching module B, the scene coping module C respectively adopts different methods to obtain the interference scene SP_now＝(l_now,s_now) Corresponding recovery scheme p_now. When a certain element SP does not exist in the scenario library SP_jSo as to be connected with SP_now＝(l_now,s_now) When they are highly similar (i.e. are

) Then real-time response operation is used to obtain SP_now＝(l_now,s_now) Corresponding recovery scheme p_now. Otherwise, extracting and SP_now＝(l_now,s_now) Highly similar elements SP_jCorresponding recovery scheme p_jAnd adjusting the data by applying a heuristic adjusting algorithm to obtain a final recovery scheme p_now。

C.1 the details of the real-time response operation therein are as follows.

C.1.1 first of all according to the original flight plan, SP, of the airline company_nowS to be restored in_nowConstructing a structure including s under the conditions of maximum allowable delay time, shortest turnaround time between two adjacent flights and time dispersion of a space-time network_nowA model of the spatiotemporal network of all aircraft and associated flights. The network model specifically comprises two arcs of different types, namely flight arcs and stay arcs; three different space-time points, namely a source node, an intermediate node and a receiving point.

C.1.2 according to interference scenarios SP_now＝(l_now,s_now) The flight network generated in c.1.1 determines the set of flight arcs that are directly affected, and it is not noted df. Then, df and relevant parameters (such as flight cancellation cost, unit time delay cost and the like) of the original flight plan are substituted into a pure airplane flow network model for solvingAll flight sets affected by the ripple effect of the flight network are obtained (denoted as Df, which is more than or equal to Df).

C.1.3 then determines the interfered passenger travel sets related to the Df according to the Df, and generates route sets (denoted as Tl) which can be switched for the travels respectively according to the space-time network generated in C.1.1 under the condition that the shortest connection time required by two adjacent flights is met and the airports are the same.

And C.1.4, on the basis of obtaining Df, Tl and parameters related to the flights and the passengers, constructing an airplane and passenger integrated interference recovery model, and acquiring a recovery scheme by using commercial solving software. If the interfered flight set in the recovery scheme is consistent with the Df, the solution is completed, the scheme is the final recovery scheme, if the interfered flight set is not consistent with the Df, the C.1.2 is returned to repeat the relevant steps, the route set capable of changing the sign is rearranged for the journey of the passenger which is not considered to be interfered, and the updated optimal sign changing scheme is obtained by applying an airplane and passenger integrated interference recovery model in the C.1.3.

The details of the pure airplane flow network model mentioned in c.1.2 are as follows:

(objective function):

in the pure airplane flow network model, the goal mainly consists of minimizing the flight delay cost and the flight cancellation cost for the airline. N is a radical of_fIndicating the number of passengers in the flight f. c. C_fIndicating the flight f cancellation cost.

And a flight arc formed by the time-space points i and j and representing whether the airplane a executes the flight f or not, wherein the value of 1 represents yes. y is_fIndicating whether the flight f is cancelled, and the value of 1 indicates cancellation.

(model constraints):

in the above formula

Indicating whether the airplane a passes through a staying arc formed by the space-time points i and j,

representing the number of aircraft of model e that airport j ultimately needs to dock. Constraint (2) has the meaning that each flight has no plane to execute and no cancellation, and there are two and only two cases. Constraint (3) constraint (4) are aircraft flow balance constraints, where constraint (3) indicates that the number of incoming flights from a point is equal to the number of outgoing flights from that point, and constraint (4) indicates that during airport curtailment, a certain number of aircraft should be parked at each airport for normal operation of the airline the next day.

The aircraft and passenger integration model mentioned in c.1.4 has the following specific details:

(objective function):

in the airplane and passenger integrated interference recovery model, the goals mainly include minimizing the flight delay cost of the airline, helping the passenger to change the sign, and the passenger trip interruption cost. The reason for not considering the cancellation cost is the passenger trip interruption cost and the inclusion of the flight cancellation cost. Wherein c is_uvIndicating the associated unit cost, t, of re-signing a u-trip passenger to a v-trip_uvThe number of people who changed their signs is indicated.

Indicating the cost of trip u interruption，r_uThe number of people for which the trip u is interrupted.

Constraint aspects, except for the three constraints (2) - (4) that comprise the pure airplane flow network model, the remaining constraints are as follows:

w in the above formula_uAnd indicating whether the journey u receives interruption or not, and if the interruption is 1, otherwise, taking the value of 0. N is a radical of_uIndicating the number of passengers originally in the trip u.

And (4) indicating whether the journey u of the passenger contains the flight f, wherein if the flight f is contained, the value is 1, and otherwise, the value is 0. Cap_aRepresenting the maximum passenger capacity of the aircraft a. Constraints (5), (6) are used together to determine whether journey u is interrupted, and if the relevant flight in journey u is cancelled, journey u must be interrupted (meaning of constraint (5)), and if the time interval between two adjacent flights in journey u is too short, then there is no time for the passenger to make a transition and therefore also interrupted (meaning of constraint (6)). The constraint (7) is to specify that for passengers on any trip, the number of last flights to be taken plus the number of people to select a refund equals the total number of people. Constraint (8) determinationIt is defined that the number of passengers carried by any aircraft is not allowed to exceed its maximum passenger capacity. The constraint (9) specifies that the number of passengers selecting a change should be less than or equal to the number of passengers of the previous trip.

The details of the c.2 heuristic tuning algorithm are as follows.

C.2.1 preliminary adjustment. 1) First, find out l_jInterference scenario ld characteristic of_jAnd all flights involved in these unique interference scenarios are adjusted according to the original flight recovery plan. E.g. l_jThere is a flight f1500 delayed by one hour, but l_nowSince FD is not { F1500, D,60 }. epsilon.ld, it is known that FD is not { F1500, D,60 }. epsilon._jWhen the initial adjustment is performed, p can be adjusted_jThe departure time for the flight f1500 is adjusted to the original departure time for the flight and the passenger itinerary associated with the flight is also adjusted in response. 2) Finding s_jThe peculiar moiety sd of (A)_jAccording to s_nowMaking adjustments (e.g. to s)_jIs present but s_nowRemoving the missing passenger journey, and according to s_nowNumber of passengers in each journey p_jThe number of passengers in the corresponding trip is updated, etc.). The recovery scheme obtained by these operations is recorded as the initial adjustment recovery scheme and used

And (4) performing representation.

C.2.2 interference recovery range determination. The interference recovery range determination specifically comprises two parts of a flight interference recovery limit range and a passenger journey recovery limit range. 1) And determining a flight interference recovery limit range. According to l_nowInterference scenario ld specific to_now＝l_j-l_commonDetermining the affected flight sets, then determining relevant airplane sets from the flight sets, extracting flight strings executed by the airplanes on the same day as the limited range (marked as U) of the flight interference recovery_f). Assume flight f as shown in FIG. two₂The Airport affected by the disturbance then includes Airport in particular₂And Airport₃And Airport₂、Airport₃The associated aircraft includes aircraft A, B, C, so the flight string executed by aircraft A, B, C on that day is for flight f₂And (4) recovering the limited range of the flight interference determined by the interference II. 2) The passenger journey recovery limited range is determined according to the journey contained in the range limited by the flight interference recovery (marked as U)_I). In fig. two is the set of itineraries associated with all flights performed by the aircraft A, B, C.

C.2.3 acquisition of final recovery scheme. 1) First recover from preliminary adjustments to the scenario

In which this part is eliminated and noted

And according to U_fEstablishing a space-time network model to recover a limited range U for passenger journey interference_IThe route of the signature can be changed after the arrangement. 2) Solving by applying airplane and passenger integrated interference recovery model in real-time response operation to obtain flight recovery scheme SU_fAnd passenger trip recovery scheme SU_I. 3) To SU_I、SU_fAnd

merging is carried out

That is, the final recovery scheme p_now。

D. A scenario evaluation module:

obtaining the existing interference scenario SP by using the C scenario response module_now＝(l_now,s_now) Corresponding recovery scheme p_nowThen, SP needs to be judged_n'_ow＝(l_now,s_now,p_now) Can be incorporated into the existing scenario-scenario library SP. For the recovery scheme obtained by adopting the real-time response operation, the elements and SP do not exist in the scene-scheme library_now＝(l_now,s_now) Are highly correlated and therefore will SP_n'_ow＝(l_now,s_now,p_now) The inclusion in the existing scenario-scenario library SP is advantageous for improving its completeness. For the recovery scheme obtained by adopting the heuristic adjustment algorithm, the elements and the SP exist in the existing scenario-scheme library SP_now＝(l_now,s_now) Highly correlated and therefore further evaluation is needed to determine whether to incorporate it into the scenario-scenario library. The specific steps are as follows:

d.1 for high matching Interval [ K₁＝0.85,1]We can divide in advance into two sub-intervals, which are respectively [ K ]₁＝0.85,K₂＝0.925]、(K₂＝0.925,1]。

D.2 according to the scene matching module, calculating the elements and SP in the scene-scheme library_nowMatching is performed with values falling within intervals [ K ]₁＝0.85,K₂＝0.925](K₂＝0.925,1]The number of (2) is respectively denoted as N₁,N₂。

D.3 order N_now＝N₁+N₂，N_nowFor the situation-scenario library SP with the SP_now＝(l_now,s_now) The number of elements with high matching exists, and NH is the maximum number of fields with high matching degree, which is set to be equal to 5 in the invention. If N is present₂≧ NH, then the algorithm terminates without regard for its inclusion into the scenario solution library. Otherwise if N is₂< NH, then a random number is randomly generated, accepted with a probability of ε, where

δ is a scale control influencing factor, which is set to 0.8 in the present invention, and the larger the value, the smaller the overall scale of SP).

In the actual operation process, the specific steps required by the invention are as follows:

(1) in an idle period (non-interference period) of an airline company, interference scenes which occur in the past of the airline company are collected and interference scenes which possibly occur in the future are predicted, an interference recovery scheme corresponding to the interference scenes is obtained by using a scene coping method, and then a scene evaluation module is adopted to judge whether the interference scenes and the recovery schemes corresponding to the interference scenes are necessary to be included in a scene-scheme library so as to expand the completeness of the interference scenes and the recovery schemes.

(2) When an airline is affected by an existing interference event, a corresponding interference scenario (airport interference, airplane interference or flight interference) and an object to be recovered, namely an SP, are first determined from the interference event_now＝(l_now,s_now). And then, a situation matching module which is firstly entered in the framework is used for directly establishing a mathematical model for interference recovery, which is different from the previous research. The module is mainly used for judging whether elements exist in the scene-scheme library or not and judging whether existing interference scenes SP exist in the scene-scheme library or not_now＝(l_now,s_now) And if the element exists, extracting the recovery scheme corresponding to the element, and applying a heuristic adjustment algorithm corresponding to the scenario response module to obtain a final recovery scheme. The efficiency of the method is far more than that of directly establishing a mathematical model for solving. And if the current situation does not exist, adopting the real-time response operation in the situation coping module at the moment to obtain the final recovery scheme.

(3) When the final recovery scheme has been acquired and used in the actual recovery process, it is then necessary to determine the interference scenario SP_now＝(l_now,s_now) And a recovery scheme p corresponding thereto_nowThere is no need to incorporate into the scenario-scenario library. And at the moment, continuing to call the scene evaluation module for evaluation.

(4) When the airline is again affected by the interference event, the above steps can be repeated to obtain an airplane and passenger integrated interference recovery scheme.

The above details describe the present invention, an optimization decision framework based on context-handling. From the implementation effect, for 188 airplanes and 630 flight shifts, 65710 passengers and 687 passenger travel numbers (wherein, the single travel is 630, and the two travels are 57), the final recovery scheme can be obtained within 31.088 seconds, and the practical requirements of the airline company can be met.

The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (7)

1. An optimization decision system for airplane and passenger integrated interference recovery based on scenario response is characterized in that: the system comprises a scene-scheme library construction module, a scene matching module, a scene coping module and a scene evaluation module;

the scene-scheme library construction module is used for constructing past and predicted interference scenes possibly suffered by an airline company in the future and a recovery scheme corresponding to the interference scenes to generate a scene-scheme library SP; each element in the scenario-solution library SP is an SP_i＝(l_i,s_i,p_i)；l_iA tag indicating a type of interference; s_iRepresenting the attributes of the interference recovery object, specifically comprising the number flt _ size of the fleet to be recovered and the travel plan iti _ size of the related passengers; p is a radical of_iThen the corresponding recovery scheme is indicated;

the scenario matching module is used for the scenario SP when the airline company suffers from the existing interference_now＝(l_now,s_now) Upon impact, label l according to interference type_nowAnd interference recovery object attribute s_nowRapidly matching with elements in a scene-scheme library SP, and judging whether highly similar elements exist or not;

the situation coping module is used for acquiring a recovery scheme corresponding to the interference situation suffered by the airline company according to the interference situation; if the situation matching module judges that the situation SP exists in the pre-generated situation-scheme library SP and interferes with the situation SP_now＝(l_now,s_now) Highly similar elements SP_jThen the scenario reply module adjusts SP_jRecovery scheme p in (1)_jTo acquire the data corresponding to the interference scenario SP_nowOf the final recovery scheme p_now(ii) a If the elements with the similar height are not matched, the scene response module carries out real-time response operation, and an airplane and passenger integrated interference recovery model is established to solve an optimal recovery scheme;

the scene evaluation module is used for updating and maintaining the scene-scheme library SP.

2. The system of claim 1, wherein the system comprises: the method for generating the scenario-scenario library SP in the scenario-scenario library construction module specifically comprises the following steps:

step 1.1: setting interference type label l_i；

The interference type labels are divided into three types, namely airport interference ED, airplane interference AD and flight interference FD; interference situations common to airlines can be represented by an interference type label l ═ { ED, AD, FD }; when there is no interference of a certain type, setting it as an empty set phi;

wherein airport interference is represented by the symbols ED { (AR), (TW), (L) }; AR represents airport sequence number; TW represents an interference time window; l represents the capacity loss proportion of the takeoff or landing runway of the airport, when L is 1, the airport is completely closed, and any airplane is not allowed to take off and land;

the airplane disturbance is represented by the symbols AD { (AC), (TW) }, AC represents the airplane serial number; TW represents a time window in which the aircraft is disturbed;

flight interference is represented by symbols FD { (f), (DT) }, where f represents the interfered flight number; DT represents the type of disturbance, including both delayed flight takeoff D or cancellation C;

step 1.2: determining an interference recovery object attribute s_i；

Let DS (l)_now) Representing an interfered scenario l_nowInfluence is related to the size of the fleet, and flt _ size is determined_nowAt least, flt _ size should be satisfied_now≥DS(l_now) To ensure that all interfered flights are taken into account; with flt _ size, considering that different fleets are allowed to interchange lanes under certain conditions_nowThe cancelled flight may be executed by an airplane of another model and is not cancelled finally, so that a better recovery scheme is obtained, but at the same time, the recovery difficulty is increased sharply, so that the recovery scheme cannot be obtained in a short time, and therefore, the recovery scheme cannot be obtained in the short timeUnder the framework, the interference recovery object attribute s_iIs determined when flt _ size ≧ DS (l)_now) The condition (1) is an over-parameter and needs to be seized by an airline company;

step 1.3: determining an interference recovery scheme p_i。

3. The system of claim 2, wherein the system comprises: in the context-scheme library construction module, on the basis of creating the context-scheme library SP, in order to accelerate the existing interference context SP_nowAnd respectively setting 3 sub-libraries for the SP libraries at the speed of subsequent matching with the scenario scheme library SP, wherein the first sub-library sorts all elements in the SP by airport sequence numbers according to airport interference, the second sub-library sorts all elements in the SP by airport sequence numbers according to airplane sequence numbers, and the third sub-library sorts all elements according to flight sequence numbers.

4. The system of claim 3, wherein the system comprises: the scene matching module is used for labeling l according to the interference type_nowAnd interference recovery object attribute s_nowThe method for rapidly matching with the elements in the scenario-scenario library SP and judging whether highly similar elements exist specifically comprises the following steps:

step 2.1: defining a matching degree formula;

defining an inner matching formula and an outer matching formula, the inner matching formula being used for pair s_nowMatching is performed, defined as:

if and only if s_now＝＝s_jWhen the sizes of the fleets related to the recovery object are the same, the internal matching degree is 1;

in terms of the external matching formula, according to l_nowThere are three different interference scenarios, namelyDefining different similarity formulas:

A. airport interference similarity formula:

B. airplane interference similarity formula:

C. flight interference similarity formula:

D. the outer matching similarity formula:

formula A is a matching degree formula of airport interference, wherein a belongs to SP_now(ED) denotes extraction of SP_nowRelated elements of (1) about airport interference scenarios; | a | represents the number of flights directly affected by airport interference; [ start ]_a,end_a]An interference time window representing an existing airport interference scenario; [ start ]_b,end_b]Then represents the interference time window of the matched element; if the two interference time windows are identical, then

lq_aRepresenting an airport capacity loss value; if (a ═ b) indicates whether or not the airport is the same;

the formula B is a matching degree formula of the airplane interference, wherein | | | c | | | represents the number of flights directly affected by the airport interference; if (c) represents whether the aircraft is the same airplane or not;

formula C is a flight interference matching degree formula, where del (f) represents the delay time of flight f; the is _ same (f, h) function represents that whether the two flights are consistent or not is judged, if so, the value is 1, otherwise, the value is 0;

denominator | | SP in formula D_nowI represents the number of all flights directly affected by the existing interference scenario, and the numerator is the sum of the matching values of the three interference scenarios; the definition of the formula A, B, C can ensure that the O _ match (SP)_now,SP_j)∈[0,1]；

Step 2.2: defining a matching algorithm;

according to the existing interference scenario SP_nowRespectively calculating the flight number influenced by the ED, AD and FD, respectively marking as | | a | |, | c |, and | | | f |, and calculating the corresponding weight w_||a||、w_||b||、w_||c||：

If w is_||a||Relative to w_||b||、w_||c||If larger, then SP will be_nowThe elements of the middle ED and the first sub-library are firstly subjected to interference similarity function P according to the airport_ED(SP_now,SP_j) Calculating, and taking the object with the top rank as a candidate object; then the SP is put again_nowThe AD element in (1) and the candidate object carry out an airplane interference similarity function P_AD(SP_now,SP_j) Calculating, selecting the top-ranked as new candidate, and selecting SP_nowFD element of (1) and new candidate object carry out flight interference similarity function P_FD(SP_now,SP_j) Calculating, and selecting the object with the top rank as a final candidate object; finally, an external matching formula O _ match (SP) is applied_now,SP_j) The final candidate is compared with the SP_nowPerforming matching calculation, and determining whether highly similar element SP exists according to the size of the first-ranked matching value_j；

If w is_||a||、w_||b||、w_||c||Numerical values of the threeIf the phase difference is not large, adopting a parallel computing method to respectively convert the SP_nowThe ED element in the first sub-library is matched with the first sub-library, the AD element is matched with the second sub-library, and the FD element is matched with the third sub-library; collecting the intersection of the three candidate sets generated respectively to observe whether the intersection is empty; if the result is null, indicating that no object which is highly matched with the SP library exists; otherwise, applying an external matching formula O _ match (SP)_now,SP_j) The intersection element is compared with the SP_nowPerforming matching calculation, calculating a total matching value, and determining whether highly similar elements SP exist according to the size of the first-ranked matching value_j。

5. The system of claim 1, wherein the system comprises: in the scenario response module, if the highly similar elements are not matched, the scenario response module performs real-time response operation, and the method for establishing the airplane and passenger integrated interference recovery model to solve the optimal recovery scheme specifically comprises the following steps:

step 3.1: constructing an original flight arc and a delayed flight arc for each flight by applying a time-space network technology according to an original flight plan of an airline company;

step 3.2: according to interference scenarios SP_now＝(l_now,s_now) Determining a flight arc set directly affected with the flight network generated in the step 3.1, and recording the flight arc set as df; substituting the Df and related parameters of the original flight plan into a pure aircraft flow network model for solving to obtain all flight sets influenced by a ripple effect of a flight network, and recording the flight sets as Df; determining the interfered passenger travel sets related to the Df according to the Df, and respectively generating route sets which can be changed and are marked as Tl for the travel sets according to the flight network generated in the step 3.1, the shortest connection time required by two adjacent flights and the condition that the airports are the same;

step 3.3: on the basis of obtaining Df, Tl and parameters related to flights and passengers, an airplane and passenger integrated interference recovery model is constructed, and a recovery scheme is solved; if the interfered flight set in the recovery scheme is consistent with the Df, the solution is completed, and the scheme is a final recovery scheme; otherwise, returning to step 3.2, the route set which can be re-signed is re-arranged for disturbed passenger trips not considered before.

6. The system of claim 1, wherein the system comprises: in the scenario correspondence module, if the highly similar elements are matched, a heuristic adjustment algorithm is adopted, and SP is adjusted_jRecovery scheme p in (1)_jTo acquire the data corresponding to the interference scenario SP_nowOf the final recovery scheme p_now；

Step 4.1: according to interference labels l_jAnd l_nowAnd an object to be restored s_jAnd s_nowIs applied to the initial interference recovery scheme p_jPerforming preliminary adjustment;

step 4.1.1: find out l_jIn a particular interference scenario, by symbols

Is represented by_nowAnd l_jSame interference scenario between, ld_j＝l_j-l_commonIs represented by_jThe flight recovery method comprises the following steps of (1) adjusting all flights involved in the special interference scenarios according to an original flight recovery plan;

step 4.1.2: finding s_jAccording to s_nowMaking an adjustment by a symbol

Denotes s_nowAnd s_jSame moiety between, sd_j＝s_j-s_nowDenotes s_jA specific interference scenario; to s_jIs present but s_nowRemoving the missing passenger journey according to s_nowNumber of passengers in each journey p_jUpdating the corresponding number of passengers; the obtained preliminary adjustment recovery schemeIs marked as

Step 4.2: determining an interference recovery range, including a flight interference recovery limit range and a passenger journey recovery limit range; since the initial adjustment recovery scheme is already available

Therefore, the final recovery scheme p is obtained by adopting a local optimization mode without optimizing all flights and passenger trips_now；

First according to_nowInterference scenario ld specific to_now＝l_now-l_commonDetermining the affected flight sets, then determining related aircraft sets from the flight sets, extracting flight strings executed by the aircraft on the current day as a flight interference recovery limit range, and recording the flight strings as U_f(ii) a Determining the passenger journey recovery limit range according to the journeys contained in the range limited by the flight interference recovery, and recording the range as U_I；

Step 4.3: acquiring a final recovery scheme;

step 4.3.1: restoring a schema from preliminary adjustment

Middle eliminating U_fAnd U_IIs marked as

Is U_fEstablishing a spatio-temporal network model for all flights in the set as U_IThe passenger itineraries contained in the set are arranged and the route can be changed;

step 4.3.2: solving by applying airplane and passenger integrated interference recovery model in real-time response operation to obtain flight recovery scheme SU_fAnd traveler's trip recovery SU_I；

Step 4.3.3: to SU_I、SU_fAnd

merging is carried out

Get the final recovery scheme p_now。

7. The system of claim 1, wherein the system comprises: the method for updating and maintaining the scenario-scheme library SP in the scenario evaluation module specifically comprises the following steps:

if in the scene matching module, SP_now＝(l_now,s_now) If there is no highly similar element after matching with the scenario-scenario library SP, the recovery scenario p obtained in the scenario response module is recovered_nowTogether, adding the two into a scenario-scheme library SP;

if in the scene matching module, SP_now＝(l_now,s_now) Highly similar elements exist after matching with the scenario-scenario library SP; then the following steps are performed:

step 5.1: for highly similar interval [ K₁,1]Is divided into two subintervals, respectively being [ K₁,K₂]、[K₁,1]；

Step 5.2: obtaining the elements in the scene-scheme library SP and SP calculated by the scene matching module_nowRespectively fall within the interval [ K ]₁,K₂]And [ K ]₁,1]The number of (2) is respectively denoted as N₁,N₂；

Step 5.3: let N be equal to N₁+N₂，NK₂The maximum number of fields with high matching degree; if N is present₂≥NK₂Then do not consider its inclusion in the scenario solution library; if N is present₂＜NK₂A random number is generated, accepted with a probability of epsilon,

delta is a scale control influence factor, and the larger the value is, the scene-squareThe smaller the overall size of the library SP.

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