CN111079008B - Scheme recommendation method and system for taxi driver to leave in storage pool - Google Patents
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Abstract
The invention provides a scheme recommendation method and a system for a taxi driver to leave in a storage pool. The scheme recommendation method for the taxi driver to leave in the storage pool comprises the steps of constructing a decision evaluation matrix according to a leaving decision scheme faced by the taxi driver and evaluation indexes in each leaving decision scheme, and normalizing the decision evaluation matrix; screening out an optimal decision scheme and a worst decision scheme in the normalized decision evaluation matrix; calculating boundary distances between the evaluation index and the optimal decision scheme and the worst decision scheme respectively
And
calculating the close value c of the evaluation index and each stay decision scheme i The expression is:
wherein i is more than or equal to 1 and less than or equal to m, and m is the number of leaving decision schemes facing a taxi driver; for the value of closeness c i Ordering, wherein the affinity value c i The smaller the corresponding leaving decision scheme is, the better the evaluation result is; will be the close value c i And recommending and giving a taxi driver for the leave decision scheme corresponding to the minimum value.
Description
Technical Field
The invention belongs to the field of scheme recommendation for removing and reserving in a storage tank, and particularly relates to a scheme recommendation method and system for removing and reserving in the storage tank by a taxi driver.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
Because the airport or the high-speed rail station is generally far away from urban areas, particularly, the public transportation modes such as airports, buses, subways and the like are inconvenient, passengers carry more luggage, and the public transportation stops at night and the like, the airport taxis are the main transportation modes after the passengers arrive at the ground hub. The airport separates the passenger delivering (departure) and the passenger receiving (arrival) channels, and the passenger delivering taxi driver faces the problem of leaving a 'storage pool', namely, the taxi driver must choose between waiting for receiving the passenger in the 'storage pool' and returning the empty taxi to the urban passenger.
The inventor finds that at present, for judging that the 'vehicle storage pool' is left, a driver often judges which selection brings greater benefit to the driver by virtue of past experience, but the subjective decision often has greater uncertainty, so that greater imbalance is brought to the benefit of the driver, and the design and distribution of the 'vehicle storage pool' lanes and parking points of an airport are also influenced.
Disclosure of Invention
In order to solve the above problems, a first aspect of the present invention provides a method for recommending a solution for a taxi driver to stay in a pool, which considers the close values between the evaluation indexes in the stay decision solutions and the respective stay decision solutions, screens out the optimal stay decision solution and recommends to give a taxi driver according to the smaller close values, and realizes the decision making for the greater benefit of the taxi driver and the automatic recommendation of the stay decision solution.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a scheme recommendation method for a taxi driver to leave in a storage pool includes:
constructing a decision evaluation matrix according to the leaving decision schemes faced by the taxi drivers and the evaluation indexes in each leaving decision scheme, and normalizing the decision evaluation matrix;
screening out an optimal decision scheme and a worst decision scheme in the normalized decision evaluation matrix;
calculating boundary distance d between evaluation index and optimal decision scheme and worst decision scheme respectively i + and di - ；
Calculating the close value c of the evaluation index and each stay decision scheme i The expression is:
wherein i is more than or equal to 1 and less than or equal to m, and m is the number of leaving decision schemes facing a taxi driver;
for the value of closeness c i Ordering, wherein the affinity value c i The smaller the corresponding leaving decision scheme is, the better the evaluation result is; will be the close value c i And recommending and giving a taxi driver for the leave decision scheme corresponding to the minimum value.
In order to solve the above problems, a second aspect of the present invention provides a solution recommendation system for a taxi driver to stay in a storage pool, which considers the close values between the evaluation indexes in the stay decision solutions and the respective stay decision solutions, screens out the optimal stay decision solution and recommends to give a taxi driver according to the better evaluation results of the corresponding stay decision solutions as the close values are smaller, and realizes the decision making for helping the taxi driver to make a benefit-greater decision and the automatic recommendation of the stay decision solution.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a solution recommendation system for a taxi driver to stay in a storage pool, comprising:
the decision evaluation matrix construction and standardization module is used for constructing a decision evaluation matrix according to the leaving decision schemes faced by the taxi driver and the evaluation indexes in each leaving decision scheme and carrying out standardization processing on the decision evaluation matrix;
the optimal and worst decision scheme screening module is used for screening out the optimal decision scheme and the worst decision scheme in the normalized decision evaluation matrix;
a boundary distance calculating module for calculating boundary distances between the evaluation index and the optimal decision scheme and the worst decision scheme respectively
and />
；
A close value calculation module for calculating the close value c of the evaluation index and each stay decision scheme i The expression is:
wherein i is more than or equal to 1 and less than or equal to m, and m is the number of leaving decision schemes facing a taxi driver;
a leave-out decision scheme recommendation module for recommending the affinity value c i Ordering, wherein the affinity value c i The smaller the corresponding leaving decision scheme is, the better the evaluation result is; will be the close value c i And recommending and giving a taxi driver for the leave decision scheme corresponding to the minimum value.
In order to solve the above-mentioned problems, a third aspect of the present invention provides a computer readable storage medium, which considers the close values between the evaluation index in the stay decision schemes and each stay decision scheme, and according to the smaller close values, the better the evaluation results of the corresponding stay decision schemes, screens out the best stay decision schemes and recommends to give a taxi driver, thereby realizing the decision for helping the taxi driver to make greater benefit and the automatic recommendation of the stay decision schemes.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps in a method of proposal recommendation for taxi drivers to stay in a pool as described above.
In order to solve the above problems, a fourth aspect of the present invention provides a computer device, which considers the close values between the evaluation index in the stay decision schemes and each stay decision scheme, and screens out the best stay decision scheme and recommends to give a taxi driver according to the better evaluation result of the corresponding stay decision scheme as the close value is smaller, thereby realizing the decision for helping the taxi driver to make greater benefit and the automatic recommendation of the stay decision scheme.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps in the method of taxi driver stay in pool recommendation as described above when the program is executed.
The beneficial effects of the invention are as follows:
according to the leaving decision schemes facing taxi drivers and the evaluation indexes in each leaving decision scheme, a decision evaluation matrix is constructed, and the decision evaluation matrix is subjected to standardization processing; screening out an optimal decision scheme and a worst decision scheme in the normalized decision evaluation matrix; calculating boundary distance d between evaluation index and optimal decision scheme and worst decision scheme respectively i - Calculating the close values of the evaluation index and each retention decision scheme, and sequencing according to the close values, wherein the smaller the close value is, the better the evaluation result of the corresponding retention decision scheme is; and recommending the leaving decision scheme with the close value being the minimum value to the taxi driver, so that the taxi driver is assisted to make decisions for maximizing the benefit of the taxi driver and the automatic recommendation of the leaving decision scheme is realized.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention.
FIG. 1 is a flow chart of a proposal recommending method for a taxi driver to stay in a storage pool according to an embodiment of the invention;
FIG. 2 is a graph of factor indicators influencing the selection of a driver decision scheme in accordance with an embodiment of the present invention;
FIG. 3 is a weather indicator of an embodiment of the present invention.
Detailed Description
The invention will be further described with reference to the drawings and examples.
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present invention. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
Example 1
Fig. 1 is a flowchart of a scheme recommendation method for a taxi driver to leave in a storage pool according to the embodiment.
The following describes in detail, with reference to fig. 1, the implementation procedure of the scheme recommendation method for the taxi driver to leave in the storage pool according to the embodiment:
as shown in fig. 1, the scheme recommendation method for removing the taxi driver from the storage pool in this embodiment includes:
step S101: constructing a decision evaluation matrix according to the leaving decision schemes faced by the taxi drivers and the evaluation indexes in each leaving decision scheme, and normalizing the decision evaluation matrix;
in a specific implementation, two core factors of driver income and passenger number are considered, wherein the driver income comprises a cost index, a benefit index and a fixity index; the number of passengers includes the number of flights arriving per unit time and the passenger rate. The cost index comprises fuel consumption and personal income tax, the benefit index comprises passenger carrying mileage and passenger carrying times, and the fixity index comprises contractor cost and parking cost of a storage pool. The number of flights arriving per unit time is affected by weather conditions, seasons, and day and night, and the occupancy rate includes peaks and low peaks.
The taxi driver benefits are influenced by the necessary expenditure such as the number of passengers, the waiting time, the driving mileage of the passengers, the oil consumption, the total amount of the fare, the personal income tax, the taxi contract fee and the like, and the waiting fee in the storage pool, wherein the driving mileage of the passengers and the number of the passengers are obviously positively correlated with the taxi benefits, and the waiting time and the oil consumption are negatively correlated with the driver benefits. In general, the total amount of the vehicle fee increases, and the driver's profits increase; the more expense is incurred in entering the reservoir, the lower the revenue. But in comparison, the cost of entering the vehicle storage pool has less negative relevant influence on the income of a driver; the taxi contract cost is a necessary expenditure, and has objectivity; the fuel consumption and the personal income tax are necessary expenditure, the expenditure is positively correlated with the driving mileage, and further positively correlated with the income of a driver, but the positive correlation degree is lower relative to the driving mileage.
Through checking taxi charging standards, taxi charging is divided into two charging standards of daytime and nighttime, the taxi charging is obtained by related data, passenger taxi taking cost is distributed in a piecewise function according to different mileage, and the following two piecewise functions are obtained through calculation and are shown in formulas (1) and (2):
wherein x represents mileage; f (f) 1 Indicating daytime charges; f (f) 2 Indicating night tolls.
The total cost W is defined as shown in equation (3):
W＝c+d+m+T (3)
(3) Wherein: c is oil consumption; d is the cost required for entering the vehicle storage pool; m is taxi contractual fee; t is the time cost.
The driver net income P is defined as shown in formula (4):
P＝f-W (4)
(4) Wherein: f is the total income of the driver.
The system can calculate the taxi taking cost and the consumed time cost obtained by the driver according to the taxi driving mileage and the waiting time, wherein the longer the waiting time is, the larger the time cost is, and the net benefit obtained by the driver can be calculated according to the formula (4) by combining the payable taxi contractor fee of the taxi driver, the fee entering the storage pool and the like, if the net benefit is higher than a certain fixed value, the driver selects a certain scheme (namely entering the storage pool to wait for passengers), and if the net benefit is lower than a certain fixed value, the driver selects another scheme (namely, the direct empty vehicle returns to the urban passenger).
Let the driver face m decision schemes of leaving, there are n evaluation indexes in each scheme, then decision evaluation matrix R is:
in the process of normalizing the decision evaluation matrix:
for the benefit index: a, a ij ＝x ij /maxx ij ；(5)
For the cost index: a, a ij ＝minx ij /x ij ；(6)
wherein ,xij For decision evaluation of elements in the matrix, a ij The elements in the matrix are evaluated for the normalized policy.
The waiting time and the oil consumption are the cost indexes, the driving mileage of the passenger is the benefit index, and the taxi contract cost is the fixed index. The net benefit of the taxi driver is equal to the passenger's taxi-taking fee minus the total cost (time cost + taxi-taking fee + personal income tax + waiting fee in the pool + fuel consumption).
And then calculating a decision matrix after normalization processing:
step S102: screening out an optimal decision scheme and a worst decision scheme in the normalized decision evaluation matrix;
the optimal decision scheme at this time is:
the worst decision scheme is: a is that - ＝(y 1 - ,y 2 - ,...,y m - ) (10)
The number of elements of the optimal decision scheme and the worst decision scheme is m, and the number is equal to the total number of the leaving decision schemes facing the driver; the element in the optimal decision scheme is the maximum value in each row of elements in the normalized decision evaluation matrix; the element in the worst decision scheme is the minimum value in each row of elements in the normalized decision evaluation matrix.
Step S103: calculating boundary distances between the evaluation index and the optimal decision scheme and the worst decision scheme respectively
And
in specific implementation, the boundary distance between the evaluation index and the optimal decision scheme and the worst decision scheme are calculated
and />
The formula of (2) is:
wherein ,
the elements in the optimal decision scheme set; />
Is an element in the worst decision scheme set; a, a ij Representing a j-th normalized evaluation index corresponding to an i-th leaving decision scheme faced by a taxi driver as an element in the normalized decision evaluation matrix; n is the number of evaluation indicators in each withholding decision scheme.
Step S104: calculating the close value c of the evaluation index and each stay decision scheme i The expression is:
wherein i is more than or equal to 1 and less than or equal to m, and m is the number of leaving decision schemes facing a taxi driver;
step S105: for the value of closeness c i Ordering, wherein the affinity value c i The smaller the corresponding leaving decision scheme is, the better the evaluation result is; will be the close value c i And recommending and giving a taxi driver for the leave decision scheme corresponding to the minimum value.
According to the value of closeness c i Size ordering of c i The smaller the scheme is, the better the evaluation result is, which indicates that the decision scheme is supposed to have more flights, fewer front queuing cars and other influencing factors in the time period are basically in an acceptable range, so that the probability that taxi drivers choose to enter an airport to queue and carry passengers is higher; conversely, c i The smaller the evaluation result is, the worse the evaluation result is, and the larger the probability that the driver returns to the urban passenger.
The comparison of the schemes of the factors of the data decision matrix adopted in this example, as shown in fig. 2, affects the factor index selected by the driver decision scheme. The driver is faced with the conditions that the passenger carrying travel is long (30/km), the waiting time is long (0.6 h), the number of passengers is flat, the weather belongs to a low cloud state, the passenger carrying travel is short (10/km), the waiting time is short (0.25 h), the passenger carrying travel is long, the weather belongs to a low cloud state, the passenger carrying rate exceeds the first preset threshold, the passenger carrying travel is short (8/km), the waiting time is short (0.2 h), the passenger carrying peak period is high, the weather is good, the passenger carrying travel is long (25/km), the waiting time is long (1 h), the passenger carrying rate is low, the weather belongs to a low cloud state, and the passenger carrying rate is generally (exceeds a second preset threshold and is smaller than the first preset threshold), wherein the possibility of waiting for arriving at a waiting area to return to the urban area is queued under the condition that the second preset threshold is less than the first preset threshold. Fig. 3 shows the weather conditions in the evaluation index.
The ideal situation that the driver goes to the arrival area and waits for the passenger to return to the urban area is that the degree of closeness between the four classical situations and the ideal situation is respectively given, so the driver is faced with the selection of four situations:
TABLE 1 decision scheme index
Obviously this is a multi-objective decision problem for multi-factor indicators. The decision evaluation matrix is as follows:
the waiting time and the oil consumption are cost indexes, the driving mileage of the passenger is a benefit index, and the taxi contract cost is a fixed index. The net benefit of the taxi driver is equal to the passenger's taxi-taking fee minus the total cost (time cost + taxi-taking fee + personal income tax + waiting fee in the pool + fuel consumption).
The matrix after normalization can be calculated from the above as:
the optimal decision scheme at this time is: a is that + ＝(1,1,1,1,1)；
The worst decision scheme is: a is that - ＝(1/5,4/15,4/7,5/8,5/8)；
And further, the calculation can be obtained:
calculating a close value:
the smaller the close value is, the better the evaluation result is, and the final evaluation result is: c > B > A > D.
In other embodiments, in order to verify the stability of the system and the benefit of the decision model, the situation that the taxi driver waits for passengers at the airport can be generalized by using a close value method, so as to obtain A, B, C, D, E, F, G, H, I schemes comprising longer waiting time of the driver, longer journey, middle peak of flights, better weather, better passenger seat rate, shorter waiting time of the driver, shorter journey, peak of flights, better weather and high passenger seat rate. The specific conditions after the quantization scheme is carried out on each index of the scheme are shown in the following table:
TABLE 2 decision matrix factors
The scheme recommendation method flow for removing the taxi driver from the storage pool shown in fig. 1 is utilized to obtain the nine schemes with the following close values: 0.85409,0.28813,0.27516,1.0374,1.1051,1.5674,0,1.3297,0.55395. The close value of the G scheme is 0, so that the gain of a driver of the G scheme is highest, the situation that waiting time, driving mileage, weather, number of flights and passenger seat rate are all good or excellent is known by the G scheme, and according to practical experience, the situation is the optimal situation encountered by a taxi driver, and the driver should choose to wait. The situation that the close value is counted is C, B, I scheme, and the decision scheme given by the comprehensive C, B, I scheme is as follows: under the conditions of good weather state and more flights, no matter how far or near the passengers take, the drivers can get good benefit in unit time.
The scheme with large comprehensive analysis value can be obtained, and under the conditions of poor weather state, less number of flights and low passenger seat rate, the driver has less income, but the situation that passengers with longer passenger journey can be received and better income is obtained is not excluded. Under the condition, the driver can comprehensively consider the number of the taxis waiting in the storage pool to make a decision, for example, if the number of the taxis in the storage pool is more, the driver can select to return to the city, and if the number of the taxis in the storage pool is less, the driver can select to continue waiting.
Example 2
The embodiment provides a scheme recommendation system for a taxi driver to leave in a storage pool, which comprises:
(1) The decision evaluation matrix construction and standardization module is used for constructing a decision evaluation matrix according to the leaving decision schemes faced by the taxi driver and the evaluation indexes in each leaving decision scheme and carrying out standardization processing on the decision evaluation matrix;
(2) The optimal and worst decision scheme screening module is used for screening out the optimal decision scheme and the worst decision scheme in the normalized decision evaluation matrix;
(3) A boundary distance calculating module for calculating boundary distances between the evaluation index and the optimal decision scheme and the worst decision scheme respectively
and />
Specifically, in the boundary distance calculation module, the boundary distance between the evaluation index and the optimal decision scheme and the worst decision scheme respectively is calculated
and />
The formula of (2) is:
wherein ,
the elements in the optimal decision scheme set; />
Is the worstAn element in the policy schema collection; a, a ij Representing a j-th normalized evaluation index corresponding to an i-th leaving decision scheme faced by a taxi driver as an element in the normalized decision evaluation matrix; n is the number of evaluation indicators in each withholding decision scheme.
(4) A close value calculation module for calculating the close value c of the evaluation index and each stay decision scheme i The expression is:
wherein i is more than or equal to 1 and less than or equal to m, and m is the number of leaving decision schemes facing a taxi driver;
(5) A leave-out decision scheme recommendation module for recommending the affinity value c i Ordering, wherein the affinity value c i The smaller the corresponding leaving decision scheme is, the better the evaluation result is; will be the close value c i And recommending and giving a taxi driver for the leave decision scheme corresponding to the minimum value.
The decision evaluation matrix construction and normalization module is used for reserving evaluation indexes in the decision scheme, wherein the evaluation indexes comprise cost indexes, benefit indexes and fixed indexes.
In the decision evaluation matrix construction and normalization module, in the process of normalizing the decision evaluation matrix:
for the benefit index: a, a ij ＝x ij /maxx ij ；
For the cost index: a, a ij ＝minx ij /x ij ；
wherein ,xij For decision evaluation of elements in the matrix, a ij The elements in the matrix are evaluated for the normalized policy.
Example 3
The present embodiment provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of a method of proposal recommendation for taxi drivers to stay in a pool as shown in fig. 1.
Example 4
The present embodiment provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, which when executed implements steps in a method for recommending a solution for taxi drivers to stay in a pool as shown in fig. 1, it should be understood by those skilled in the art that embodiments of the present invention may be provided as a method, a system, or a computer program product. Accordingly, the present invention may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, magnetic disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program stored on a computer readable storage medium, which when executed may comprise the steps of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random access Memory (Random AccessMemory, RAM), or the like.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. The scheme recommendation method for the taxi driver to leave in the storage pool is characterized by comprising the following steps of:
constructing a decision evaluation matrix according to the leaving decision schemes faced by the taxi drivers and the evaluation indexes in each leaving decision scheme, and normalizing the decision evaluation matrix;
screening out an optimal decision scheme and a worst decision scheme in the normalized decision evaluation matrix;
calculating boundary distances between the evaluation index and the optimal decision scheme and the worst decision scheme respectively
and />
Calculating the close value c of the evaluation index and each stay decision scheme i The expression is:
wherein i is more than or equal to 1 and less than or equal to m, and m is the number of leaving decision schemes facing a taxi driver;
for the value of closeness c i Ordering, wherein the affinity value c i The smaller the corresponding leaving decision scheme is, the better the evaluation result is; will be the close value c i Recommending and giving a taxi driver for the leave decision scheme corresponding to the minimum value;
calculating boundary distances between the evaluation index and the optimal decision scheme and the worst decision scheme respectively
and />
The formula of (2) is:
wherein ,
the elements in the optimal decision scheme set; />
Is an element in the worst decision scheme set; a, a ij Is the element in the normalized decision evaluation matrix and represents the first face of taxi driversi evaluating indexes after j th norms corresponding to the decision removing schemes, wherein the total number of the evaluating indexes in the decision evaluating matrix is m; n is the number of evaluation indicators in each withholding decision scheme.
2. The method for recommending a solution for a taxi driver to stay in a pool according to claim 1, wherein the evaluation indexes in the stay decision-making solution include a cost type index, a benefit type index and a fixed type index.
3. The method for recommending a solution for a taxi driver to leave in a pool according to claim 2, wherein, in the process of normalizing the decision evaluation matrix:
for the benefit index: a, a ij ＝x ij /maxx ij ；
For the cost index: a, a ij ＝minx ij /x ij ；
wherein ,xij For decision evaluation of elements in the matrix, a ij The elements in the matrix are evaluated for the normalized policy; the total number of evaluation indexes in the decision evaluation matrix is m; the total number of the stay decision schemes in the decision evaluation matrix is n.
4. A taxi driver stay in pool solution recommendation system for executing and completing a taxi driver stay in pool solution recommendation method according to any one of claims 1-3, comprising:
the decision evaluation matrix construction and standardization module is used for constructing a decision evaluation matrix according to the leaving decision schemes faced by the taxi driver and the evaluation indexes in each leaving decision scheme and carrying out standardization processing on the decision evaluation matrix;
the optimal and worst decision scheme screening module is used for screening out the optimal decision scheme and the worst decision scheme in the normalized decision evaluation matrix;
the boundary distance calculation module is used for calculating the difference between the evaluation index and the optimal decision scheme and the worst decision scheme respectivelyBoundary distance of (2)
and />
A close value calculation module for calculating the close value c of the evaluation index and each stay decision scheme i The expression is:
wherein i is more than or equal to 1 and less than or equal to m, and m is the number of leaving decision schemes facing a taxi driver;
a leave-out decision scheme recommendation module for recommending the affinity value c i Ordering, wherein the affinity value c i The smaller the corresponding leaving decision scheme is, the better the evaluation result is; will be the close value c i And recommending and giving a taxi driver for the leave decision scheme corresponding to the minimum value.
5. The scheme recommendation system for taxi drivers to stay in a pool according to claim 4, wherein in the boundary distance calculation module, boundary distances between the evaluation index and the optimal decision scheme and the worst decision scheme, respectively, are calculated
And
the formula of (2) is:
wherein ,
the elements in the optimal decision scheme set; />
Is an element in the worst decision scheme set; a, a ij Representing j-th normalized evaluation indexes corresponding to the i-th leaving decision scheme faced by a taxi driver as elements in the normalized decision evaluation matrix, wherein the total number of the evaluation indexes in the decision evaluation matrix is m; n is the number of evaluation indicators in each withholding decision scheme.
6. The taxi driver stay-away solution recommendation system in a pool of claim 4, wherein the decision-making and evaluation matrix construction and normalization module is configured to keep the evaluation indicators in the decision-away solution including a cost indicator, a benefit indicator and a fixed indicator.
7. The solution recommendation system for taxi drivers to stay in a pool of cars according to claim 6, wherein in the decision evaluation matrix construction and normalization module, in the process of normalizing the decision evaluation matrix:
for the benefit index: a, a ij ＝x ij /maxx ij ；
For the cost index: a, a ij ＝minx ij /x ij ；
wherein ,xij For decision evaluation of elements in the matrix, a ij The elements in the matrix are evaluated for the normalized policy; the total number of evaluation indexes in the decision evaluation matrix is m; the total number of the stay decision schemes in the decision evaluation matrix is n.
8. A computer readable storage medium having stored thereon a computer program, which when executed by a processor performs the steps in the method of claim 1-3.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein execution of the program by the processor effects the steps in the method of claim 1-3 for taxi driver stay in pool recommendation.
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