CN109019056A - A kind of Container Yard bilayer aerial conveyor vertical transport equipment dispatching method - Google Patents
A kind of Container Yard bilayer aerial conveyor vertical transport equipment dispatching method Download PDFInfo
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- CN109019056A CN109019056A CN201810987500.7A CN201810987500A CN109019056A CN 109019056 A CN109019056 A CN 109019056A CN 201810987500 A CN201810987500 A CN 201810987500A CN 109019056 A CN109019056 A CN 109019056A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G63/00—Transferring or trans-shipping at storage areas, railway yards or harbours or in opening mining cuts; Marshalling yard installations
- B65G63/002—Transferring or trans-shipping at storage areas, railway yards or harbours or in opening mining cuts; Marshalling yard installations for articles
- B65G63/004—Transferring or trans-shipping at storage areas, railway yards or harbours or in opening mining cuts; Marshalling yard installations for articles for containers
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G43/00—Control devices, e.g. for safety, warning or fault-correcting
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G2201/00—Indexing codes relating to handling devices, e.g. conveyors, characterised by the type of product or load being conveyed or handled
- B65G2201/02—Articles
- B65G2201/0235—Containers
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Abstract
The invention discloses a kind of Container Yard bilayer aerial conveyor vertical transport equipment dispatching methods.This method sets the condition of container vertical transport equipment scheduling model first, then it is that objective function establishes storage yard container vertical transport equipment intelligent scheduling model that it is most short in the stockyard waiting time, which to complete whole tasks in for a period of time with container level transporting equipment, container level transporting equipment is completed whole tasks and is made of altogether five parts in the stockyard waiting time in for a period of time, every part determines whether to count according to different vertical transport tasks again, then the constraint condition of intelligent scheduling model objective function has been determined, and the model is solved using the Hybrid Particle Swarm of fusion BP algorithm.
Description
Technical field
The present invention relates to the crane scheduling field in harbour container stockyard, in particular to a kind of Container Yard is double-deck high
Mounted track vertical transport equipment dispatching method.
Background technique
The technique side that traditional container terminal mostly uses greatly rubbertyred container gantry crane (RTG) cooperation truck
Formula, since same case area RTG occupies identical path, the RTG that same case area is equipped with is few.Relatively large Container Yard
Mostly use mixed heap, with the same working method unloaded of dress, when several bridges of distribution go to complete several vertical transport tasks, they
Movement need to spend more time between the area Nei Xiang of stockyard, in order to improve the vertical transport efficiency in entire stockyard, both at home and abroad at present
The intelligent dispatching method of some Container Yard internal fields bridge is developed.
Mixed-integer programming model is current most commonly used Container Yard field bridge scheduling model, takes case to make to minimize
The linear combination of industry deadline lead and access casing working deadline retardation is target, determine the distribution of task and
Task ranking scheme；In addition to this it is dispatched again there are also field bridge scheduling model, robust pre-scheduling complex reaction based on weak rock mass
The field bridge scheduling model of strategy, the model established according to actual needs including some other.And the optimization algorithm of solving model is then
It mainly include genetic algorithm, ant group algorithm, simulated annealing and heuritic approach etc..
Respectively have advantage and disadvantage in the intelligent scheduling of above-mentioned model and algorithm bridge on the scene, but none be not be used in it is traditional with
Gantry container crane adds in the technology mode of truck, but what full-automatic container terminal involved in the present invention used
It is the technology mode for automating the double-deck aerial conveyor vertical transport equipment and adding automatization level transporting equipment, wherein full-automatic packaging
Case vertical transport equipment and traditional gantry container crane are different by the walking of big mechanism of car, using aerial conveyor,
Container lifting device is walked on aerial conveyor, is arranged by height track frame, and same case area can arrange more lifting
Equipment.The equipment and technology mode used due to full-automatic container terminal is all far from each other with conventional container harbour,
Existing scheduling model and algorithm improper application.
Summary of the invention
The purpose of the present invention is to provide a kind of Container Yard bilayer aerial conveyor vertical transport equipment dispatching methods, reach
To the purpose for carrying out rational management to multiple devices, shortening the equipment waiting time, improving operating efficiency.
The present invention realizes that its technical purpose technical solution is: a kind of Container Yard bilayer aerial conveyor vertical transport equipment
Dispatching method is established for using the full-automatic container terminal machinery and process characteristic of the double-deck aerial conveyor vertical transport equipment
The scheduling model and the corresponding optimization algorithm of use of new container vertical transport equipment solve it.
In the full-automatic Container Yard using the double-deck aerial conveyor vertical transport equipment, automatization level transporting equipment
(including automatic guided vehicle, LIFT AGV, automatic straddle carrier, unmanned truck etc.) container level is transported to pile case area or
Stockyard is transported, more aerial conveyor container lifting devices are equipped in same case area and container is realized in horizontal trasportation equipment cooperation
Vertical transport operation, aerial conveyor container lifting device can load a container and walk in case area, thus with water
Flat transporting equipment can be done directly first to unload case and case again and work twice in once docking.
The present invention proposes for a kind of intelligent method to be used for be realized in such automatic cabinet stockyard with double-deck high in case area
The scheduling of mounted track container vertical transport equipment reaches and carries out full-automatic rational management to multiple devices, shortens equipment waiting
Time, the purpose for improving operating efficiency.This method most short establishes stockyard in the stockyard waiting time with horizontal trasportation equipment for target
Container vertical transport equipment intelligent scheduling model, and the model is solved using the Hybrid Particle Swarm of fusion BP algorithm, side
Method includes the following steps:
Step A, container vertical transport equipment intelligent scheduling model foundation condition is set
1) each container vertical transport equipment work capacity is identical；
2) production plan of Container Yard operation and prestowage plan have determined that；
3) area Ge Xiang only one berth of horizontal trasportation equipment；
4) all container vertical transport equipments in same case area can reach all berths in case area；
5) container vertical transport equipment once promotes a 20ft TEU (Twenty-foot Equivalent Unit)；
6) mould turnover operation has terminated, wait case always in top layer；
Step B, intelligent scheduling model objective function is determined:
T is that container level transporting equipment reaches berthing assignment to the total time for leaving berth, intelligent scheduling in n task
The target of model realizes that t is minimum.
Wherein, ti1Targeted containers position to be installed is reached from current location for container vertical transport equipment in i-th of task
Set the time；ti2To grab the targeted containers time in i-th of task；ti3For container vertical transport equipment in i-th of task from
It grabs case position and reaches required time above container level transporting equipment；ti4It is transported for vanning in i-th of task to container level
The transfer device time；ti5To unload the case time from container level transporting equipment in i-th of task；ti0For container in i-th of task
The time required to vertical transport equipment is directly reached from current location above container level transporting equipment.α, β and γ are coefficient, respectively
From value it is as follows:
Assuming that the container vertical transport equipment sum that can work in case area is N；It is with container level transporting equipment berth
Benchmark, the current berth equipment k are Xki(k=1,2,3 ..., N), the targeted containers berth to be installed of the i-th task are Yi；Container
Berth spacing is DB；The big vehicle speed of vertical transport equipment is vG.Then:
Wherein i=1,2,3 ..., n.
If container vertical transport equipment suspender is apart from the total high H in groundT；The targeted containers number of plies to be installed is Fi；Each packaging
The a height of h of case layer；Vertical transport equipment lifting mechanism speed is vH；Suspender lock box time and unlocked time are fixed, respectively tLWith
tUL.Then:
If container level transporting equipment berth and case area edge distance are DP, then:
It is t if container vertical transport equipment trolley is fixed in the time of the traversing 20ft container in crossbeam directionT；
Container level transporting equipment height is HA, then:
Wherein i=1,2,3 ..., n, a is coefficient here, and value is as follows:
Step C, the constraint condition of intelligent scheduling model objective function is determined
Parameter in container vertical transport equipment intelligent scheduling model needs to meet following some constraints or perimeter strip
Part:
Equipment current location XkiAnd targeted containers position to be installed is YiThe case area inland sea berth Ce Daolu Ce Zong cannot be exceeded
Number, if from extra large side to land side case section length direction berth number being M, then:
Container vertical transport equipment suspender is apart from the total high H in groundTIt needs beyond two layers of the total number of plies of container, if container
Total number of plies is L, then:
HT≥(L+2)h
And the targeted containers number of plies to be installed should be not more than the total number of plies of container, i.e. Fi≤L。
Step D, above-mentioned scheduling model is solved using the Hybrid Particle Swarm of fusion BP algorithm
The Hybrid Particle Swarm for merging BP algorithm is based on standard particle group's algorithm.
Standard particle group algorithm is made of following two formula, wherein (1) formula is known as rate equation, (2) formula is known as position equation:
Wherein: d=1,2,3 ..., D, i=1,2,3 ..., N.
Above-mentioned two formula indicates there be n particle in the search space of D dimension, wherein the current location of i-th of particle is
xid, present speed vid.Remember i-th of particle search to optimal location be denoted as pid, optimal location that entire population searches
It is denoted as pgd, then pgdReferred to as globally optimal solution.
K is current iteration number in standard particle group's algorithm expression formula (1) and (2) formula；c1And c2It is Studying factors, is non-
Negative constant, the value generally between 0-2, wherein c1Adjust the step-length that particle flies to itself optimal location, c2Adjust particle to
The step-length of global optimum position flight.γ1And γ2It is the random number between [0,1], and mutually indepedent, for keeping the more of group
Sample；In order to reduce a possibility that particle leaves search space during evolution, vidIt generally defines in a certain range, i.e.,
vid∈[-vmax, vmax], vmaxIt is the constant of sets itself, i.e. the speed of particle is limited in a maximum speed vmaxIn range.
ω in expression formula (1) is inertia weight, for coordinating the global and local optimizing ability of elementary particle algorithm, is used to
Property weights omega is determined by following formula:
In formula, ωmaxWith ωminIt is the minimum and maximum weight of ω, typical value ω respectivelymax=0.9~1.4, ωmin
=0.4；K is current evolutionary generation, kmaxIt is maximum evolutionary generation.2λFor momentum, and
Merge the Hybrid Particle Swarm of BP algorithm is exactly to carry out standard particle group algorithm optimization first, if having passed through
When dry generation evolution is reached near global optimum's result, the individual for therefrom randomly selecting population carries out BP algorithm of neural network to institute
The further accurate optimization of parameter is obtained, local area deep-searching is carried out.
Container vertical transport equipment scheduling model is solved using the Hybrid Particle Swarm of fusion BP algorithm, purpose is just
It is that one reasonable vertical transport equipment of each loading and unloading task configuration makes all to appoint in container terminal work plan to be
Total time needed for business is completed is minimum；For each task in multiple tasks, there are many allocation plans of equipment, in derivation algorithm
In particle indicate an allocation plan, with equipment currently in the berth of berth and task object in case area in case area
The distance between express, that is, be that i-th of task configures kth platform equipment, in intelligent scheduling model objective function come
Expression, which is also particle current location x in algorithmidExpression formula；One group of particle in various configurations scheme formation algorithm,
A referred to as particle vector, wherein allocation optimum scheme is exactly the globally optimal solution p in algorithmgd, it is required that in objective function
Total time t be minimum.The solution procedure of model is as follows:
Step D1, the basic parameter in initialization algorithm；
Determine the initial position of particle, i.e., according to usual or Experiences first by being manually that each task configuration one is set
It is standby, and various configurations scheme is set, form one group of particle；
The initial velocity of particle optimization, the initial value of inertial factor ω, grain are determined according to the recommended method in standard particle group
Maximum allowable iterative steps k in swarm optimizationmax, Studying factors c1And c2Value.
Step D2, the optimal solution p that the current location of each particle is just used as particle itself currentid, i.e., current every group is set
Allocation optimum is all regarded in standby configuration as；Vertical transport equipment intelligent scheduling model objective function is directlyed adopt as particle swarm algorithm
Fitness function, the initial fitness of each particle is calculated according to each parameter of initialization, that is, calculates every group of configuration and completes packaging
Casing working required by task total time t.
Step D3, it chooses and completes container operation required by task total time t the smallest one group of device configuration in all configurations
Scheme conduct is current optimal, that is, chooses the best conduct global extremum p of extreme value in all individual particlesgd, the corresponding pole of the particle
Value is exactly the optimal value of scheduling model in next iteration；
Acquisition global extremum pgdIt brings into algorithm expression formula formula (1) and formula (2), as soon as a group new particle can be calculated,
It is to obtain a set of new equipment configuration scheme determined by algorithm.
Step D4, the required total time for recalculating every kind of scheme in new allocation plan, that is, each new particle is reappraised
Fitness, the stored best particle of the worst particle of fitness replaces, if current location is compared in the new position of i-th of particle
pidIt is good, then using new position as the optimal location of current particle, if the best values in the new position of all new particles are better than current
Global optimum pgd, then pgdIt is replaced by that best position in all new particles, that is, reselects institute in new departure
Need total time the smallest as updated optimal case.
If step D5, pgdValue change is very small, as the p that adjacent iteration twice obtains occur in continuous several timesgdDifference it is exhausted
It is less than given minimum numerical constant δ to value, then selects a particle at random from current particle group and begin to use BP algorithm in pgd
Local area deep-searching is nearby carried out, the worst particle in current particle group is replaced with the result of BP search.
Step D6, inertial factor ω is updated according to formula (3), is executed repeatedly since step D4 again, until reaching maximum
Until allowing the number of iterations or meeting objective function requirement, the global extremum obtained at this time is the optimal solution of scheduling model,
The equipment scheduling scheme of its corresponding working equipment, that is, system optimization of each task.
Below with reference to drawings and examples, the present invention is described in detail.
Detailed description of the invention
Fig. 1 is full-automatic Container Yard equipment arrangement signal of the present invention using the double-deck aerial conveyor vertical transport equipment
Figure.
Specific embodiment
Use the full-automatic Container Yard of the double-deck aerial conveyor vertical transport equipment as shown in Figure 1: 1 for container level
Transporting equipment, 2 be elevating rack mode be arranged track, 3 be container vertical transport equipment, 4 be container.Container level fortune
Container level is transported to the pile case area in stockyard or transports stockyard by transfer device, is arranged in same case area by height mounted track
Mode realizes the vertical transport operation of container equipped with 4 container lifting devices and the cooperation of container level transporting equipment,
Container vertical transport equipment is unmanned automatic equipment, can load a container when walking in case area, because
This can be done directly first to unload case and case again in once docking with container level transporting equipment and work twice.
The present invention proposes for a kind of intelligent method to be used for be realized in such Container Yard with aerial conveyor double-deck in case area
The scheduling of full-automatic container vertical transport equipment reaches and carries out rational management to multiple devices, the shortening equipment waiting time, mentions
The purpose of high operating efficiency.This method is most short for mesh in the stockyard waiting time with 25 tasks of container level transporting equipment completion
Mark establishes storage yard container vertical transport equipment intelligent scheduling model, and is solved using the Hybrid Particle Swarm of fusion BP algorithm
The model, method include the following steps:
Step S1, container vertical transport equipment intelligent scheduling model foundation condition is set
1) each container vertical transport equipment work capacity is identical；
2) production plan of Container Yard operation and prestowage plan have determined that；
3) area Ge Xiang only one berth of horizontal trasportation equipment；
4) all container vertical transport equipments in same case area can reach all berths in case area；
5) container vertical transport equipment once promotes a 20ft TEU (Twenty-foot Equivalent Unit)；
6) mould turnover operation has terminated, wait case always in top layer；
Step S2, intelligent scheduling model objective function is determined
Wherein n=25, t be in 25 tasks container level transporting equipment reach berthing assignment to leave berth it is total when
Between, the target of intelligent scheduling model realizes that t is minimum.
Wherein, ti1Targeted containers position to be installed is reached from current location for container vertical transport equipment in i-th of task
Set the time；ti2To grab the targeted containers time in i-th of task；ti3For container vertical transport equipment in i-th of task from
It grabs case position and reaches required time above container level transporting equipment；ti4It is transported for vanning in i-th of task to container level
The transfer device time；ti5To unload the case time from container level transporting equipment in i-th of task；ti0For container in i-th of task
The time required to vertical transport equipment is directly reached from current location above container level transporting equipment.α, β and γ are coefficient, respectively
From value it is as follows:
Assuming that the container vertical transport equipment sum that can work in case area is N=4；With container level transporting equipment berth
On the basis of, the current berth equipment k is Xki(k=1,2,3 ..., N), the targeted containers berth to be installed of the i-th task are Yi；Packaging
Case berth spacing is DB；The big vehicle speed of vertical transport equipment is vG.Then:
Wherein i=1,2,3 ..., 25.
If container vertical transport equipment suspender is apart from the total high H in groundT；The targeted containers number of plies to be installed is Fi；Each packaging
The a height of h=4.572m of case layer；Vertical transport equipment lifting mechanism speed is vH；Suspender lock box time and unlocked time are fixed, point
It Wei not tLAnd tUL.Then:
If container level transporting equipment berth and case area edge distance are DP, then:
It is t if container vertical transport equipment trolley is fixed in the time of the traversing 20ft container in crossbeam directionT；
Container level transporting equipment height is HA, then:
Wherein i=1,2,3 ..., 25, a is coefficient here, and value is as follows:
Step S3, the constraint condition of intelligent scheduling model objective function is determined
Parameter in container vertical transport equipment intelligent scheduling model needs to meet following some constraints or perimeter strip
Part:
Equipment current location XkiAnd targeted containers position to be installed is YiThe case area inland sea berth Ce Daolu Ce Zong cannot be exceeded
Number, if from extra large side to land side case section length direction berth number being M=40, then:
Container vertical transport equipment suspender is apart from the total high H in groundTIt needs beyond two layers of the total number of plies of container, if container
Total number of plies is L=6, then:
HT≥(L+2)h
And the targeted containers number of plies to be installed should be not more than the total number of plies of container, i.e. Fi≤L。
Step S4, above-mentioned scheduling model is solved using the Hybrid Particle Swarm of fusion BP algorithm
The Hybrid Particle Swarm for merging BP algorithm is based on standard particle group's algorithm.
Standard particle group algorithm is made of following two formula, wherein (1) formula is known as rate equation, (2) formula is known as position equation:
Wherein: d=1,2,3 ..., D, i=1,2,3 ..., N.
Above-mentioned two formula indicates there be n particle in the search space of D dimension, wherein the current location of i-th of particle is
xid, present speed vid.Remember i-th of particle search to optimal location be denoted as pid, optimal location that entire population searches
It is denoted as pgd, then pgdReferred to as globally optimal solution.
K is current iteration number in standard particle group's algorithm expression formula (1) and (2) formula；c1And c2It is Studying factors, is non-
Negative constant, the value generally between 0-2, wherein c1Adjust the step-length that particle flies to itself optimal location, c2Adjust particle to
The step-length of global optimum position flight.γ1And γ2It is the random number between [0,1], and mutually indepedent, for keeping the more of group
Sample；In order to reduce a possibility that particle leaves search space during evolution, vidIt generally defines in a certain range, i.e.,
vid∈[-vmax, vmax], vmaxIt is the constant of sets itself, i.e. the speed of particle is limited in a maximum speed vmaxIn range.
ω in expression formula (1) is inertia weight, for coordinating the global and local optimizing ability of elementary particle algorithm, is used to
Property weights omega is determined by following formula:
In formula, ωmaxWith ωminIt is the minimum and maximum weight of ω, typical value ω respectivelymax=0.9~1.4, ωmin
=0.4；K is current evolutionary generation, kmaxIt is maximum evolutionary generation；2λFor momentum, and
Merge the Hybrid Particle Swarm of BP algorithm is exactly to carry out standard particle group algorithm optimization first, if having passed through
When dry generation evolution is reached near global optimum's result, the individual for therefrom randomly selecting population carries out BP algorithm of neural network to institute
The further accurate optimization of parameter is obtained, local area deep-searching is carried out.
Container vertical transport equipment scheduling model is solved using the Hybrid Particle Swarm of fusion BP algorithm, purpose is just
It is that one reasonable vertical transport equipment of each loading and unloading task configuration makes all to appoint in container terminal work plan to be
Total time needed for business is completed is minimum；For each task in multiple tasks, there are many allocation plans of equipment, in derivation algorithm
In particle indicate an allocation plan, with equipment currently in the berth of berth and task object in case area in case area
The distance between express, that is, be that i-th of task configures kth platform equipment, in intelligent scheduling model objective function come
Expression, which is also particle current location x in algorithmidExpression formula；One group of particle in various configurations scheme formation algorithm,
A referred to as particle vector, wherein allocation optimum scheme is exactly the globally optimal solution p in algorithmgd, it is required that in objective function
Total time t be minimum.The solution procedure of model is as follows:
Step S401, the basic parameter in initialization algorithm；
Determine the initial position of particle, i.e., according to usual or Experiences first by being manually that each task configuration one is set
It is standby, and various configurations scheme is set, form one group of particle；
The initial velocity of particle optimization, the initial value of inertial factor ω, grain are determined according to the recommended method in standard particle group
Maximum allowable iterative steps k in swarm optimizationmax, Studying factors c1And c2Value.
Step S402, the optimal solution p that the current location of each particle is just used as particle itself currentid, i.e., every group current
Device configuration all regards allocation optimum as；Vertical transport equipment intelligent scheduling model objective function is directlyed adopt to calculate as population
The fitness function of method calculates the initial fitness of each particle according to each parameter of initialization, that is, calculates every group of configuration and complete collection
Vanning required by task total time t.
Step S403, completion container operation required by task total time t the smallest one group of equipment in all configurations is chosen to match
Scheme is set as current optimal, that is, choose extreme value in all individual particles it is best be used as global extremum pgd, the particle is corresponding
Extreme value is exactly the optimal value of scheduling model in next iteration；
Acquisition global extremum pgdIt brings into algorithm expression formula formula (1) and formula (2), as soon as a group new particle can be calculated,
It is to obtain a set of new equipment configuration scheme determined by algorithm.
Step S404, the required total time for recalculating every kind of scheme in new allocation plan each new grain is reappraised
The fitness of son, the stored best particle of the worst particle of fitness replaces, if present bit is compared in the new position of i-th of particle
Set pidIt is good, then using new position as the optimal location of current particle, if the best values in the new position of all new particles are better than working as
Preceding global optimum pgd, then pgdIt is replaced, that is, is reselected in new departure by that best position in all new particles
Required total time is the smallest as updated optimal case.
If step S405, pgdValue change is very small, as the p that adjacent iteration twice obtains occur in continuous several timesgdDifference
Absolute value is less than given minimum numerical constant δ, then selects a particle at random from current particle group and BP algorithm is begun to use to exist
pgdLocal area deep-searching is nearby carried out, the worst particle in current particle group is replaced with the result of BP search.
Step S406, inertial factor ω is updated according to formula (3), is executed repeatedly since step S404 again, until reaching
Maximum allowable the number of iterations or until meeting objective function requirement, the global extremum obtained at this time is the optimal of scheduling model
Solution, the equipment scheduling scheme of its corresponding working equipment, that is, system optimization of each task.
The above display describes basic principle and technical characteristics of the invention.The present invention is not by the limit of above-described embodiment
System, in the case where not departing from the principle of the invention and range, various changes and improvements may be made to the invention, these changes and improvements also belong to
The right of this patent.
Claims (3)
1. a kind of Container Yard bilayer aerial conveyor vertical transport equipment dispatching method, with container level transporting equipment in heap
It is that target establishes storage yard container vertical transport equipment intelligent scheduling model, and uses fusion BP algorithm that the field waiting time is most short
Hybrid Particle Swarm solves the model, it is characterised in that: the following steps are included:
Step A, container vertical transport equipment intelligent scheduling model foundation condition is set；
Step B, intelligent scheduling model objective function is determined:
I=1,2,3 ..., n
T is that container level transporting equipment reaches berthing assignment to the total time for leaving berth, intelligent scheduling model in n task
Target realize that t is minimum；
Wherein, ti1When reaching targeted containers position to be installed from current location for container vertical transport equipment in i-th of task
Between；ti2To grab the targeted containers time in i-th of task；ti3It is container vertical transport equipment in i-th of task from grabbing case
The time required to position reaches above container level transporting equipment；ti4It is set for vanning in i-th of task to container level transport
The standby time；ti5To unload the case time from container level transporting equipment in i-th of task；ti0It is vertical for container in i-th of task
The time required to transporting equipment is directly reached from current location above container level transporting equipment；α, β and γ are coefficient, respective
Value is as follows:
N is the container vertical transport equipment sum that can work in case area；
On the basis of container level transporting equipment berth, the current berth equipment k is Xki(k=1,2,3 ..., N), the i-th task
Targeted containers berth to be installed is Yi；Container berth spacing is DB；The big vehicle speed of vertical transport equipment is vG；
HTIt is always high apart from ground for container vertical transport equipment suspender；
FiIt is the targeted containers number of plies to be installed；
H is that each container layers are high；
vHIt is vertical transport equipment lifting mechanism speed；
tLAnd tULIt is suspender lock box time and unlocked time respectively；
DPIt is container level transporting equipment berth and case area edge distance；
Container vertical transport equipment trolley is fixed in the time of the traversing 20ft container in crossbeam direction, is tT；Packaging
Case horizontal trasportation equipment height is HA；
Step C, the constraint condition of intelligent scheduling model objective function is determined；
Step D, above-mentioned scheduling model is solved using the Hybrid Particle Swarm of fusion BP algorithm；
The Hybrid Particle Swarm for merging BP algorithm is based on standard particle group's algorithm；
Standard particle group algorithm is made of following two formula, wherein (1) formula is known as rate equation, (2) formula is known as position equation:
Wherein: d=1,2,3 ..., D, i=1,2,3 ..., N；
Above-mentioned two formula indicates there be n particle in the search space of D dimension, wherein the current location of i-th of particle is xid,
Present speed is vid；Remember i-th of particle search to optimal location be denoted as pid, optimal location that entire population searches note
For pgd, then pgdReferred to as globally optimal solution；
K is current iteration number in standard particle group's algorithm expression formula (1) and (2) formula；c1And c2Studying factors, for 0-2 it
Between nonnegative constant, wherein c1Adjust the step-length that particle flies to itself optimal location, c2Particle is adjusted to global optimum position
The step-length of flight；γ1And γ2It is the random number between [0,1], and mutually indepedent；vid∈[-vmax, vmax], vmaxIt is voluntarily to set
Fixed constant, the i.e. speed of particle are limited in a maximum speed vmaxIn range；
ω in expression formula (1) is inertia weight, is determined by following formula:
In formula, ωmaxWith ωminIt is the minimum and maximum weight of ω, typical value ω respectivelymax=0.9~1.4, ωmin=
0.4；K is current evolutionary generation, kmaxIt is maximum evolutionary generation；2λFor momentum, and
Container vertical transport equipment scheduling model is solved using the Hybrid Particle Swarm of fusion BP algorithm, is container terminal
Each loading and unloading task, which configures a reasonable vertical transport equipment, in work plan makes whole tasks complete required total time
At least；For each task in multiple tasks, there are many allocation plans of equipment, and a particle indicates in derivation algorithm
One allocation plan, with equipment currently in the berth in case area at a distance from task object is between the berth in case area come table
It reaches, that is, is that i-th task configures kth platform equipment, with expressing in intelligent scheduling model objective function, which is also to calculate
Particle current location x in methodidExpression formula；One group of particle in various configurations scheme formation algorithm, also referred to as a particle to
Amount, wherein allocation optimum scheme is exactly the globally optimal solution p in algorithmgd, it is required that total time t in objective function is most
It is small；The process for solving container vertical transport equipment scheduling model using the Hybrid Particle Swarm of fusion BP algorithm is as follows:
Step D1, the basic parameter in initialization algorithm；
It determines the initial position of particle, forms one group of particle；
The initial velocity of particle optimization, the initial value of inertial factor ω, population are determined according to the recommended method in standard particle group
Maximum allowable iterative steps k in algorithmmax, Studying factors c1And c2Value；
Step D2, the optimal solution p that the current location of each particle is just used as particle itself currentid, i.e., current every group of equipment is matched
It sets and all regards allocation optimum as；Vertical transport equipment intelligent scheduling model objective function is directlyed adopt as the suitable of particle swarm algorithm
Function is answered, the initial fitness of each particle is calculated according to each parameter of initialization, that is, calculates every group of configuration and completes container work
Industry required by task total time t；
Step D3, it chooses and completes container operation required by task total time t the smallest one group of equipment configuration scheme in all configurations
As current optimal, that is, choose extreme value in all individual particles it is best be used as global extremum pgd, the corresponding extreme value of the particle is just
It is the optimal value of scheduling model in next iteration；
Acquisition global extremum pgdIt brings into algorithm expression formula formula (1) and formula (2), one group of new particle can be calculated, exactly obtained
Obtain a set of new equipment configuration scheme determined by algorithm；
Step D4, the required total time for recalculating every kind of scheme in new allocation plan the suitable of each new particle is reappraised
Response, the stored best particle of the worst particle of fitness replaces, if the new position of i-th of particle is than current location pid
It is good, then using new position as the optimal location of current particle, if the best values in the new position of all new particles are complete better than current
Office optimal value pgd, then pgdIt is replaced, that is, reselects required in new departure by that best position in all new particles
Total time is the smallest as updated optimal case；
If step D5, pgdValue change is very small, as the p that adjacent iteration twice obtains occur in continuous several timesgdAbsolute value of the difference
Less than given minimum numerical constant δ, then selects a particle at random from current particle group and begin to use BP algorithm in pgdNear
Local area deep-searching is carried out, the worst particle in current particle group is replaced with the result of BP search；
Step D6, inertial factor ω is updated according to formula (3), is executed repeatedly since step D4 again, until reaching maximum allowable
The number of iterations or until meeting objective function requirement, the global extremum obtained at this time is the optimal solution of scheduling model, each
The equipment scheduling scheme of its corresponding working equipment, that is, system optimization of task.
2. Container Yard bilayer aerial conveyor vertical transport equipment dispatching method according to claim 1, feature exist
In: the setting container vertical transport equipment intelligent scheduling model foundation condition in the step A includes:
1) each container vertical transport equipment work capacity is identical；
2) production plan of Container Yard operation and prestowage plan have determined that；
3) area Ge Xiang only one berth of container level transporting equipment；
4) all container vertical transport equipments in same case area can reach all berths in case area；
5) container vertical transport equipment once promotes a 20ft TEU (Twenty-foot Equivalent Unit)；
6) mould turnover operation has terminated, wait case always in top layer.
3. Container Yard bilayer aerial conveyor vertical transport equipment dispatching method according to claim 1, feature exist
In: in step C: the constraint condition for determining intelligent scheduling model objective function includes:
Parameter in container vertical transport equipment intelligent scheduling model needs to meet following some constraints or boundary condition:
Equipment current location XkiAnd targeted containers position to be installed is YiThe total Berth number in the case area inland sea side Ce Daolu cannot be exceeded, if
It is M from extra large side to land side case section length direction berth number, then:
Container vertical transport equipment suspender is apart from the total high H in groundTIt needs beyond two layers of the total number of plies of container, if the total layer of container
Number is L, then:
HT≥(L+2)h
And the targeted containers number of plies to be installed should be not more than the total number of plies of container, i.e. Fi≤L。
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