CN106228243B - The station track metro depot Hui Ku arrangement method - Google Patents
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Abstract
The invention discloses a kind of station track metro depot Hui Ku arrangement methods.This method comprises the steps that library information of vehicles to be returned and station track information needed for collection algorithm first, and establishes the parameter set of practical problem；Secondly the suitable coding mode of selection is constructed to chromosome and is formulated initialization of population rule, is generated Z chromosome and is constituted initial population P；Then optimization object function and constraint are determined according to practical problem；It finally determines the selection rule of individual and the concrete operations mode of hybridization, variation, the adaptive value of each individual is calculated according to fitness function and the maximum individual of adaptive value is saved, repetitive operation is until maximum evolutionary generation.The present invention, which can rationally accept or reject train mission under resource constraint and find best station track, arranges scheme, provides decision support for subsequent daily test, shunting service, greatly improves rolling stock section's operating efficiency.
Description
Technical field
The invention belongs to technical field of rail traffic, the especially a kind of station track metro depot Hui Ku arrangement method.
Background technique
Main station section of the metro depot as subway production and transport, is mainly responsible for parking, check, reorganizing and outfit, transporting for vehicle
With with repair etc. business.It needs to stop going out to rolling stock section with Awaiting Overhaul operation or tomorrow after railcar terminates same day operation plan
Vehicle, it is significant to rolling stock section's production efficiency is improved that scientific arrangement goes back to library vehicle parking station track.The station track conventional truck Duan Huiku
It arranges to be adjusted to adjust temporarily to be conferred before each car Hui Ku according to job requirements with inspection by row to determine, it is pre- due to there is no overall arrangement to lack
Opinion property, may result in the later period return library vehicle job requirements be unable to satisfy cause operation delay or unnecessary tune
Vehicle and time-consuming, therefore consider that the station track Hui Ku is arranged to optimize with the reasonable efficient of utmostly support vehicles section operation.
There has been no the algorithm researches arranged for the station track rolling stock section Hui Ku at present, but reorganize and outfit area and passenger traffic about locomotive depot
The research that station track uses of standing arranges algorithm design to have certain reference the station track rolling stock section Hui Ku.Ji Lixia is directed to machine
The station track Arrangement Problem in area is reorganized and outfit in business section field personnel, proposes the self-adapted genetic algorithm based on N × M two-dimensional chromosome encoding, easily
It operates and has good convergence precision；Zhang Yinggui, with the condition that should be abided by, is sorted according to railway passenger station station track using the modern times
Theory, building station track application plan work out order models automatically, the application plan of passenger station station track are optimized.JW Chung
A kind of genetic algorithm based on mixed-integer programming model is proposed, is solved under rolling stock section's capacity and service ability constraint
Vehicle dispatching problem.Algorithm above is arranged and is not suitable for the station track rolling stock section Hui Ku, reality should be arranged to carry out it in conjunction with station track
It adjusts and is applied.
Summary of the invention
The purpose of the present invention is to provide a kind of simple, station track efficient metro depot Hui Ku arrangement methods.
Realizing the technical solution of the object of the invention is: a kind of station track metro depot Hui Ku arrangement method, including with
Lower step:
Step 1, library information of vehicles to be returned and station track information are collected, and establishes the parameter set of practical problem；
Step 2, chromosome constructs: on the basis of analyzing the station track Hui Ku Arrangement Problem coding requirement, selecting coding mode
Chromosome is constructed；
Step 3, initialization population P: the practical formulation initialization of population rule in library is returned in conjunction with vehicle, and is generated according to the rule
Z chromosome constitutes initial population P；
Step 4, it calculates fitness and saves optimum individual: determining the optimization object function and constraint that the station track Hui Ku arranges,
The adaptive value of each individual is calculated according to fitness function, and the maximum individual of adaptive value is saved；
Step 5, it selects, hybridize, variation: coding mode, the initialization criterion arranged for the station track Hui Ku, the choosing to individual
The concrete operations mode for selecting rule and hybridization, variation is determined；
Step 6, it generates next-generation population P: according to the selection, hybridization, variation rule determined in step 5, being selected from population
Z individual is hybridized out, mutation operation and preservation are into new population；
Step 7, termination condition: repeating step 4 to step 6 until reaching maximum evolutionary generation, optimal saved at this time
Body is the optimal solution of the solved problem of algorithm, pick up according to the optimal solution station track metro depot Hui Ku can be realized
Optimum arrangements.
Further, library information of vehicles to be returned described in step 1 include license number, whether Hui Ku, vehicle location, institute's sport car
It is secondary, return the library time, return library sequence, tomorrow whether run morning peak, whether carwash, whether daily test, park station track type, tomorrow whether
It is online；Station track information includes station track title, station track type, occupancy situation and station track coding；The parameter set of practical problem includes: kind
Group's scale Z, probability of crossover pc, mutation probability pm, maximum evolutionary generation.
Further, chromosome described in step 2 constructs, specifically: it, will using a gene as an available station track
Train returns library sequence filling to indicate track occupied；Available Necessary Number of Tracks when daily vehicle time library is indefinite, so according to reality
Situation dynamic in border constructs chromosome, constructs chromosome with the coding mode of one-dimensional matrix, each of chromosome all with
A certain available station track number is corresponding.
Further, initialization population P described in step 3, specifically:
(3.1) library vehicle to be returned is traversed, library vehicle number is obtained back and station track requires and returns the successive of library time according to expectation
Vehicle is numbered；
(3.2) determination can use station track state: when same station track A-share, B strands can be used, A-share state is that 1., 2. B strands is；
When A-share occupies, B strands available, 3. B strand state is；When B bursts of occupancy, A-share are available, 4. A-share state is；
(3.3) determine that vehicle returns the rule of library number filling chromosome:
There is the vehicle of daily test operation for night, 1., 2., 4. or other stocks for having trench the state that can park station track is
Road；
There is the vehicle of carwash operation for night, 1., 2., 3. can park station track state is；
For that need to arrange morning peak tomorrow or have the vehicle of specified train number, 1., 4. the state that can park station track is；
For there is tomorrow system to repair the vehicle of operation, can park station track is the station track for having protective net and trench；
There is the specified vehicle for parking station track type for other, the station track of corresponding types is arranged to be parked；
For having the vehicle of two and the above job requirements, can park station track will seek the requirement of all individual event operations station track
Intersection is ranked up upkeep operation requirement by importance when it is empty for can parking station track intersection, and it is low to cancel part significance level
Job requirements or job content, job requirements importance is ranked up: daily test > system repair and other station track types it is specified >
Carwash operation > morning peak or specified train number；
(3.4) station track is inserted according to the rule selection in (3.3) and available station track state is updated, be repeated up to institute
Need back library vehicle and inserts chromosome；
(3.5) (3.4) are repeated until generating Z chromosome constitutes initial population P.
Further, fitness is calculated described in step 4 and saves optimum individual: determining optimization object function and constraint,
The adaptive value of each individual is calculated according to fitness function, and the maximum individual of adaptive value is saved, specific as follows:
(4.1) constraint condition is determined, wherein constraint condition includes time interval constraint and metro depot service ability
Constraint；
(4.2) determine objective function: optimization aim is task completeness highest, and the process that picks up number of always shunting is minimum, vehicle
Go out storage convenience highest；
(4.3) fitness function is determined；
(4.4) adaptive value of each individual is calculated according to fitness function, and the maximum individual of adaptive value is saved.
Further, selection, hybridization described in step 5, variation: quasi- for the coding mode of the station track Hui Ku arrangement, initialization
Then, the concrete operations mode of the selection rule of individual and hybridization, variation is determined, specific as follows:
(5.1) the selection rule for determining individual, the individual of crossover operation is used for using roulette in selected population, if kind
The adaptive value of k-th of individual is F in groupk, then the selected probability P of k-th of individualkAre as follows:
(5.2) determine individual crossover operation mode, hybrid process the following steps are included:
Step 1: to Z/2 to it is individual each generate one (0,1] random number, if random number is less than probability of crossover pcThen into
Row crossover operation, it is on the contrary then without hybridization, save directly as new individual into new population；
Step 2: being randomly generated two [0, N for the individual that needs hybridizetrack) integer as hybridization location, to every
A parent selectes hybridization portion；
Step 3: the hybridization portion of first parent and the hybridization portion of second parent are interchangeable；
Step 4: removing all trains repeated time library serial number in the original gene of offspring from generating；
Step 5: carrying out completion to the gene for generating offspring according to initialization of population principle, and new individual is saved to new
In population；
Step 6: repeating the first step~the 5th step until new population scale reaches Z；
(5.3) determine individual mutation operation mode, mutation process the following steps are included:
Step 1: it is each to individual every in new population generate one (0,1] random number, if random number is less than mutation probability pm
Then carry out mutation operation, it is on the contrary then without mutation operation；
Step 2: being randomly generated two [0, N for the individual that needs make a variationtrack) integer as catastrophe point, and will dash forward
Genic value in height swaps；
Step 3: executing second step~third step in all individuals of population.
Further, step (4.1) the determining constraint condition, wherein constraint condition includes time interval constraint and subway
The constraint of rolling stock section's service ability, in which:
Time interval is constrained, there are two types of situations altogether:
Situation a, first train elder generation Hui Ku are parked in A-share progress daily test operation, and operation is adjusted to B strands after the completion, and A-share empties
Second train of subsequent continued access, during first train entirely picks up, daily test time-consuming 40min, shunt time-consuming 30min, therefore
Time library time interval of first and second train is more than or equal to 70min；When returning library time interval less than 70min, B strands of vehicles
Daily test task be unable to complete, directly stop to B strands；
Situation b, first train first pass through washing track and dock to A-share progress daily test operation from dextrad, adjust after the completion of operation
To B strands, A-share empties second train of subsequent continued access, during first train entirely picks up, carwash time-consuming 15min, and daily test
Time-consuming 40min, shunt time-consuming 30min, therefore time library time interval of first and second train is more than or equal to 85min；When
Time library time interval of one and second train abandons carwash task and only carries out daily test less than 85min and when being greater than 70min；
When time library time interval of first and second train are less than 70min, abandon daily test task and only carry out carwash；
Constraint for metro depot service ability, same time shunt number of tasks no more than 1, and it is same when every other day
It examines vehicle number and is not more than 3, it may be assumed that
Wherein, NdiFor the vehicle number of same time daily test；NdcFor the number of tasks of shunting of same time.
Further, step (4.2) the determining objective function: optimization aim is task completeness highest, picks up process
Number of always shunting is minimum, and vehicle goes out to be put in storage convenience highest, and wherein task completeness highest has the first importance, shunts secondary
Number at least has the second importance, and being put in storage convenience highest out has third importance；For target zj(j=1,2,3) it reaches
The priority arrived and each target need sub-goal to be achieved, and the expression formula of objective function is as follows:
Wherein, lexmin, which is represented, minimizes target according to lexicographic order；m0Represent sub-goal quantity；Represent i-th of mesh
Mark is more than expected overgauge variable；I-th of target is represented more than expected minus deviation variable；Representative is distributed to's
Positive weights；Representative is distributed toNegative weight；
For task completeness highest, if objective function is z1, z1There are 4 sub-goals: daily test completion rate of the plan highest, vehicle
It parks station track type and its operation station track requires matching degree highest, carwash completion rate of the plan highest, morning peak station track to require
With degree highest, the highest objective function z of task completeness1Are as follows:
Wherein, TiuFor the unfinished number of tasks of i-th of sub-goal；X is penalty coefficient；To distribute to each sub-goal
Negative weight；
It is minimum for number of shunting, if objective function is z2, be both needed to park and if only if two strands of A, B of same station track to
Return library vehicle and B strand vehicles needs and can daily test when, need to carry out shunting service, the least objective function z of number of shunting2
Are as follows:
z2=Tdc
Wherein, TdcFor number of actually shunting；
For going out storage convenience highest, if objective function is z3, z3Have 2 sub-goals: storage it is additional it is time-consuming at least with
And outbound is additional time-consuming minimum, is put in storage the highest objective function z of convenience out3Are as follows:
z3=Trk+Tck
Wherein, TrcFor time-consuming number outside storage total value；TckFor number time-consuming outside outbound total value；
In conclusion the catalogue scalar functions I of the station track Hui Ku Arrangement Problem are as follows:
Work as z1=0, z2=0, z3When=0, it is required optimal solution that station track corresponding to I, which arranges scheme,.
Further, step (4.3) the determining fitness function, comprising the following steps:
Step 1: calculating target value, there are 3 objective functions for each individual, i.e.,
Step 2: being ranked up according to the first priority target functional value to individual；If certain individuals are having the same
Target function value is then compared the second priority target function, and so on；If certain individuals can not finally sort,
It is then randomly ordered；Individual is arranged according to the raised sequence of target function value in this way；
Step 3: being each individual xkThe adaptive value based on sequence is distributed, if rkIt is individual xkPut in order, according to
It is as follows that a given parameter a ∈ (0,1) of family defines the adaptation value function based on sequence:
Compared with prior art, the present invention its remarkable advantage is: (1) meeting the station track rolling stock section Hui Ku and arrange practical, operation
It simply, can quickly be library vehicle allocation to be returned station track；(2) rationally train mission can be accepted or rejected, and finds out resource constraint item
The optimal station track vehicle Hui Ku scheme, is all substantially better than artificial arrangement under part either in efficiency or in reasonability.
Detailed description of the invention
Fig. 1 is the flow chart of the station track metro depot Hui Ku of the present invention arrangement method.
Fig. 2 is available station track State Encoding Style schematic diagram.
Fig. 3 be need to consider back library time interval pick up scheme schematic diagram.
Fig. 4 is certain depot's conspectus.
Fig. 5 is proxy target function tendency chart in embodiment 1.
Specific embodiment
Present invention is further described in detail with reference to the accompanying drawing.
In conjunction with Fig. 1~3, the station track metro depot Hui Ku of the present invention arrangement method, comprising the following steps:
Step 1, library information of vehicles to be returned and station track information needed for collection algorithm, and the parameter set of practical problem is established,
Wherein library information of vehicles to be returned include license number, whether Hui Ku, vehicle location, institute's sport car time, return the library time, return library sequence, tomorrow
Whether run morning peak, whether carwash, whether daily test, park whether station track type, tomorrow online etc., and station track information includes station track name
Title, station track type, occupancy situation and station track coding etc., the parameter set of practical problem includes: population scale Z, probability of crossover pc, become
Different Probability pm, maximum evolutionary generation etc..
Step 2, chromosome constructs: on the basis of analyzing the station track Hui Ku Arrangement Problem coding requirement, selecting suitable coding
Mode constructs chromosome, specifically: using a gene as an available station track, train is returned into library sequence filling with table
Show track occupied；Available Necessary Number of Tracks when daily vehicle goes back to library is indefinite, thus according to the actual situation dynamic to chromosome into
Row construction constructs chromosome with the coding mode of one-dimensional matrix, and each of chromosome is all opposite with a certain available station track number
It answers.
Step 3, initialization population P: the practical formulation initialization of population rule in library is returned in conjunction with vehicle, and is generated according to the rule
Z chromosome constitutes initial population P, the specific steps are as follows:
(3.1) library vehicle to be returned is traversed, library vehicle number is obtained back and station track requires and returns the successive of library time according to expectation
Vehicle is numbered；
(3.2) determination can use station track state.When same station track A-share, B strands can be used, A-share state is that 1., 2. B strands is；
When A-share occupies, B strands available, 3. B strand state is；When B bursts of occupancy, A-share are available, 4. A-share state is；
(3.3) Fig. 2 is combined, determines that vehicle returns the rule of library number filling chromosome:
There is the vehicle of daily test operation for night, 1., 2., 4. or other stocks for having trench the state that can park station track is
Road；
There is the vehicle of carwash operation for night, 1., 2., 3. can park station track state is；
For that need to arrange morning peak tomorrow or have the vehicle of specified train number, 1., 4. the state that can park station track is；
For there is tomorrow system to repair the vehicle of operation, can park station track is the station track for having protective net and trench；
There is the specified vehicle for parking station track type for other, the station track of corresponding types should be arranged as far as possible to be parked；
For having the vehicle of two and the above job requirements, can park station track will seek the requirement of all individual event operations station track
Intersection.When it is empty for can parking station track intersection, upkeep operation requirement need to be ranked up by importance, cancel part significance level
Low job requirements or job content.Be ranked up to job requirements importance: daily test > system is repaired and other station track types are specified
> carwash operation > morning peak or specified train number.
(3.4) station track can be inserted according to the rule selection in (3.3) and available station track state is updated, be repeated up to
Need back library vehicle and inserts chromosome.
(3.5) (3.4) are repeated until generating Z chromosome constitutes initial population P.
Step 4, it calculates fitness and saves optimum individual: determining the optimization object function and constraint that the station track Hui Ku arranges,
The adaptive value of each individual is calculated according to fitness function, and the maximum individual of adaptive value is saved, specific as follows:
(4.1) constraint condition is determined, wherein constraint condition includes time interval constraint and metro depot service ability
Constraint, in which:
In conjunction with Fig. 3, time interval is constrained, there are two types of situations altogether:
Situation a, first train elder generation Hui Ku are parked in A-share progress daily test operation, and operation is adjusted to B strands after the completion, and A-share empties
Second train of subsequent continued access, during first train entirely picks up, daily test time-consuming 40min, shunt time-consuming 30min, therefore
Time library time interval of first and second train is more than or equal to 70min；When returning library time interval less than 70min, B strands of vehicles
Daily test task be unable to complete, directly stop to B strands；
Situation b, first train first pass through washing track and dock to A-share progress daily test operation from dextrad, adjust after the completion of operation
To B strands, A-share empties second train of subsequent continued access, during first train entirely picks up, carwash time-consuming 15min, and daily test
Time-consuming 40min, shunt time-consuming 30min, therefore time library time interval of first and second train is more than or equal to 85min；When
Time library time interval of one and second train abandons carwash task and only carries out daily test less than 85min and when being greater than 70min；
When time library time interval of first and second train are less than 70min, abandon daily test task and only carry out carwash；
It is expressed as follows using formula:
Wherein TimeAjThe library time is expected back for A-share train；TimeBjThe library time is expected back for B strands of trains.
Constraint for metro depot service ability, same time shunt number of tasks no more than 1, and it is same when every other day
It examines vehicle number and is not more than 3, it may be assumed that
Wherein, NdiFor the vehicle number of same time daily test；NdcFor the number of tasks of shunting of same time.
(4.2) it determines objective function: arranging scheme to obtain the rationally efficient station track Hui Ku, optimization aim is considered as following
Several points: task completeness highest；It is minimum to pick up process number of always shunting；Vehicle goes out to be put in storage convenience highest.
Since three optimization aims have apparent priority level level, priority goal programming is considered as to solve
The station track Hui Ku decision-making problem of multi-objective, wherein task completeness highest has the first importance, obtains first and gives priority to；It shunts
Number at least has the second importance, obtains second and gives priority to；Storage convenience highest has third importance out, obtains
Third gives priority to.For target zjThe priority and each target that (j=1,2,3) reaches need sub-goal to be achieved, target
The expression formula of function is as follows:
Wherein, lexmin, which is represented, minimizes target according to lexicographic order；m0Represent sub-goal quantity；Represent i-th of mesh
Mark is more than expected overgauge variable；I-th of target is represented more than expected minus deviation variable；Representative is distributed to's
Positive weights；Representative is distributed toNegative weight；
For task completeness highest, if objective function is z1, there is 4 sub-goals: daily test completion rate of the plan highest, vehicle
It parks station track type and its operation station track requires matching degree highest, carwash completion rate of the plan highest, morning peak station track to require
With degree highest, optimally, it is desirable that each sub-goal reaches 100% completion rate, gives by sub-goal importance
The different weight of each target, since the rate that actually accomplishes of sub-goal does not exceed 100%, therefore only need toAssignment,
Respectively 1000,100,10,1.Therefore the highest objective function z of task completeness1Are as follows:
Wherein, TiuFor the unfinished number of tasks of i-th of sub-goal；X is penalty coefficient；To distribute to each sub-goal
Negative weight.
When in the same period daily test vehicle number or number of tasks of shunting be greater than constraint when, station track arrange scheme it is infeasible,
Biggish value is taken to penalty coefficient X at this time, enables X=10000, the fitness of the program is made to become smaller, then the program it is subsequent into
A possibility that being eliminated during changing will become larger.
It is minimum for number of shunting, if objective function is z2, be both needed to park and if only if two strands of A, B of same station track to
Return library vehicle and B strand vehicles needs and can daily test when, need to carry out shunting service, most ideally, it is desirable that entire
Returning in the operation of library number of shunting is 0, the least objective function z of number of shunting2Are as follows:
z2=Tdc
Wherein, TdcFor number of actually shunting；
It should be noted that two strands of A, B when same station track are both needed to park library vehicle to be returned and B strands of vehicles to include daily test
When operation, shunt when B bursts of daily test operations can be completed.
For going out storage convenience highest, if objective function is z3, have 2 sub-goals: storage is additional time-consuming minimum
And outbound is additional time-consuming minimum, most ideally, it is desirable that storage it is additional it is time-consuming be 0 with the additional time-consuming of outbound, two
Sub-goal is of equal importance, therefore goes out the storage highest objective function z of convenience3Are as follows:
z3=Trk+Tck
Wherein, TrcFor time-consuming number outside storage total value；TckFor number time-consuming outside outbound total value.
It should be noted that being put in storage total value from right side storage and when vehicle is without carwash task when vehicle goes back to library
Outer time-consuming number adds 1；A-share and if only if certain station track is unavailable or the second day that parks cars does not go out vehicle and B strands and parks cars second
When day needs vehicle out, the outer time-consuming number of outbound total value adds 1.
In conclusion the catalogue scalar functions I of the station track Hui Ku Arrangement Problem are as follows:
Work as z1=0, z2=0, z3When=0, it is required optimal solution that station track corresponding to I, which arranges scheme,.
For the trend of evolution for preferably indicating each generation population, a proxy target function I'=100z is set1+10z2+z3,
Target value is smaller to be represented closer to globally optimal solution.
(4.3) determine fitness function: adaptive value calculate the following steps are included:
Step 1: calculating target value.There are 3 objective functions for each individual, i.e.,
Step 2: being ranked up according to the first priority target functional value to individual.If certain individuals are having the same
Target function value is then compared its second priority target function, and so on.If certain individuals can not finally be arranged
Sequence then allows them randomly ordered.Individual is just lined up according to the raised sequence of target function value in this way.
Step 3: being each individual xkDistribute the adaptive value based on sequence.If rkIt is individual xkPut in order.According to
It is as follows that a given parameter a ∈ (0,1) of family defines the adaptation value function based on sequence:
(4.4) adaptive value of each individual is calculated according to fitness function, and the maximum individual of adaptive value is saved.
Step 5, it selects, hybridize, variation: coding mode, the initialization criterion arranged for the station track Hui Ku, the choosing to individual
The concrete operations mode for selecting rule and hybridization, variation is determined, specific as follows:
(5.1) the selection rule of individual is determined.This algorithm is used for of crossover operation using roulette in selected population
Body, if the adaptive value of k-th of individual is F in populationk, then the selected probability P of k-th of individualkAre as follows:
(5.2) determine individual crossover operation mode, hybrid process the following steps are included:
Step 1: to Z/2 to it is individual each generate one (0,1] random number, if random number is less than probability of crossover pcThen into
Row crossover operation, it is on the contrary then without hybridization, save directly as new individual into new population；
Step 2: being randomly generated two [0, N for the individual that needs hybridizetrack) integer as hybridization location, to every
A parent selectes hybridization portion；
Step 3: the hybridization portion of first parent and the hybridization portion of second parent are interchangeable；
Step 4: removing all trains repeated time library serial number in the original gene of offspring from generating；
Step 5: carrying out completion to the gene for generating offspring according to initialization of population principle, and new individual is saved to new
In population；
Step 6: repeating the first step to five step of step the until new population scale reaches Z.
(5.3) determine individual mutation operation mode, mutation process the following steps are included:
Step 1: it is each to individual every in new population generate one (0,1] random number, if random number is less than mutation probability pm
Then carry out mutation operation, it is on the contrary then without mutation operation；
Step 2: being randomly generated two [0, N for the individual that needs make a variationtrack) integer as catastrophe point, and will dash forward
Genic value in height swaps；
Step 3: executing second step~third step in all individuals of population.
Step 6, it generates next-generation population P: according to the selection, hybridization, variation rule determined in step 5, being selected from population
Z individual is hybridized out, mutation operation and preservation are into new population；
Step 7, termination condition: repeating step 4 to step 6 until reaching maximum evolutionary generation, optimal saved at this time
Body is the optimal solution of the solved problem of algorithm, pick up according to the optimal solution station track metro depot Hui Ku can be realized
Optimum arrangements.
Embodiment 1
Certain metro depot line arrangement schematic diagram is as shown in figure 4, vehicle enters rolling stock section, night main diamond from left
Domain is with library (4 station tracks to 16 station tracks) and maintenance library (17 station tracks to 19 station tracks), and wherein A-share road is with trench, and the station track B is without ground
Ditch, 17 to 19 station tracks be equipped with trench and protective net, vehicle can from the left or right both direction go out be put in storage, wherein dextrad go out be put in storage need through
Walk line.
The validity of verification algorithm establishes the station track metro depot Hui Ku and arranges emulation platform.Rule of thumb algorithm is joined
Number is configured, if population scale Z is 40, probability of crossover pcFor 0.8, mutation probability pmIt is for the maximum evolutionary generation of 0.1, setting
20, fitness function variable a are 0.5.State when picking up first to information of vehicles and station track counts, and shares 15 wait return
Library vehicle, and reserved 15 empty station tracks supply back library vehicle parking.Multiple target theory application genetic algorithm is then based on to time library stock
Road Arrangement Problem optimizes, and the trend of evolution of population is indicated with proxy target functional value, as shown in figure 5, algorithm is from the 8th
In generation, starts to converge to optimal solution.
The emulation of table 1 compares scheme with manual approach
Manually scheme will be arranged to be compared with the station track that emulation obtains, be shown in Table 1, simulating scheme is excellent in each index
It is arranged in artificial.In summary, under extreme conditions, this algorithm can rationally accept or reject train mission, and find out resource
The optimal station track vehicle Hui Ku scheme, is all substantially better than artificial peace under constraint condition either in efficiency or in reasonability
Row.
Claims (8)
1. a kind of station track metro depot Hui Ku arrangement method, which comprises the following steps:
Step 1, library information of vehicles to be returned and station track information are collected, and establishes the parameter set of practical problem；
Step 2, chromosome constructs: on the basis of analyzing the station track Hui Ku Arrangement Problem coding requirement, selecting coding mode to dye
Colour solid is constructed；
Step 3, initialization population P: the practical formulation initialization of population rule in library is returned in conjunction with vehicle, and generates Z according to the rule
Chromosome constitutes initial population P；
Step 4, it calculates fitness and saves optimum individual: determining the optimization object function and constraint that the station track Hui Ku arranges, according to
Fitness function calculates the adaptive value of each individual, and saves to the maximum individual of adaptive value；
Step 5, select, hybridize, variation: coding mode, the initialization criterion arranged for the station track Hui Ku advises the selection of individual
Then and the concrete operations mode of hybridization, variation is determined；
Step 6, it generates next-generation population P: according to the selection, hybridization, variation rule determined in step 5, Z is selected from population
Individual is hybridized, mutation operation and preservation are into new population；
Step 7, termination condition: step 4 is repeated to step 6 until reaching maximum evolutionary generation, the optimum individual saved at this time is i.e.
The optimal solution solved the problems, such as by algorithm, pick up according to the optimal solution the optimal of the station track metro depot Hui Ku can be realized
It arranges；
Initialization population P described in step 3, specifically:
(3.1) library vehicle to be returned is traversed, library vehicle number is obtained back and station track requires and returns the successive to vehicle of library time according to expectation
It is numbered；
(3.2) determination can use station track state: when same station track A-share, B strands can be used, A-share state is that 1., 2. B strands is；Work as A-share
It occupies, when B strand available, 3. B strand state is；When B bursts of occupancy, A-share are available, 4. A-share state is；
(3.3) determine that vehicle returns the rule of library number filling chromosome:
There is the vehicle of daily test operation for night, 1., 2., 4. or other station tracks for having trench the state that can park station track is；
There is the vehicle of carwash operation for night, 1., 2., 3. can park station track state is；
For that need to arrange morning peak tomorrow or have the vehicle of specified train number, 1., 4. the state that can park station track is；
For there is tomorrow system to repair the vehicle of operation, can park station track is the station track for having protective net and trench；
There is the specified vehicle for parking station track type for other, the station track of corresponding types is arranged to be parked；
For having the vehicle of two and the above job requirements, can park station track will seek the friendship of all individual event operations station track requirement
Collection is ranked up upkeep operation requirement by importance when it is empty for can parking station track intersection, and it is low to cancel part significance level
Job requirements or job content are ranked up job requirements importance: daily test > system is repaired and other station track types specify > are washed
Vehicle operation > morning peak or specified train number；
(3.4) station track is inserted according to the rule selection in (3.3) and available station track state is updated, be repeated up to and needed
It returns library vehicle and inserts chromosome；
(3.5) (3.4) are repeated until generating Z chromosome constitutes initial population P.
2. the station track metro depot Hui Ku according to claim 1 arrangement method, which is characterized in that described in step 1
Library information of vehicles to be returned include license number, whether Hui Ku, vehicle location, institute's sport car time, return the library time, return library sequence, tomorrow whether
Run morning peak, whether carwash, whether daily test, whether park station track type, tomorrow online；Station track information includes station track title, stock
Road type, occupancy situation and station track coding；The parameter set of practical problem includes: population scale Z, probability of crossover pc, mutation probability
pm, maximum evolutionary generation.
3. the station track metro depot Hui Ku according to claim 1 arrangement method, which is characterized in that described in step 2
Chromosome construction, specifically: using a gene as an available station track, train is returned into library sequence filling to indicate that station track accounts for
With；Available Necessary Number of Tracks when daily vehicle time library is indefinite, so dynamic constructs chromosome according to the actual situation, with
The coding mode of one-dimensional matrix constructs chromosome, and each of chromosome is all corresponding with a certain available station track number.
4. the station track metro depot Hui Ku according to claim 1 arrangement method, which is characterized in that counted described in step 4
It calculates fitness and saves optimum individual: determining optimization object function and constraint, the adaptation of each individual is calculated according to fitness function
Value, and the maximum individual of adaptive value is saved, it is specific as follows:
(4.1) constraint condition is determined, wherein constraint condition includes the constraint of time interval constraint and metro depot service ability；
(4.2) determine objective function: optimization aim is task completeness highest, and the process that picks up always is shunt, and number is minimum, and vehicle goes out
It is put in storage convenience highest；
(4.3) fitness function is determined；
(4.4) adaptive value of each individual is calculated according to fitness function, and the maximum individual of adaptive value is saved.
5. the station track metro depot Hui Ku according to claim 1 arrangement method, which is characterized in that selection described in step 5,
Hybridization, variation: coding mode, the initialization criterion arranged for the station track Hui Ku, to the selection rule of individual and hybridization, variation
Concrete operations mode be determined, it is specific as follows:
(5.1) the selection rule for determining individual, the individual of crossover operation is used for using roulette, if in population in selected population
The adaptive value of k-th of individual is Fk, then the selected probability P of k-th of individualkAre as follows:
(5.2) determine individual crossover operation mode, hybrid process the following steps are included:
Step 1: to Z/2 to it is individual each generate one (0,1] random number, if random number is less than probability of crossover pcThen hybridized
Operation, on the contrary it is then without hybridize, save directly as new individual into new population；
Step 2: being randomly generated two [0, N for the individual that needs hybridizetrack) integer as hybridization location, to each father
In generation, selectes hybridization portion；
Step 3: the hybridization portion of first parent and the hybridization portion of second parent are interchangeable；
Step 4: removing all trains repeated time library serial number in the original gene of offspring from generating；
Step 5: carrying out completion to the gene for generating offspring according to initialization of population principle, and new individual is saved to new population
In；
Step 6: repeating the first step~the 5th step until new population scale reaches Z；
(5.3) determine individual mutation operation mode, mutation process the following steps are included:
Step 1: it is each to individual every in new population generate one (0,1] random number, if random number is less than mutation probability pmThen into
Row variation operation, it is on the contrary then without mutation operation；
Step 2: being randomly generated two [0, N for the individual that needs make a variationtrack) integer as catastrophe point, and by catastrophe point
On genic value swap；
Step 3: executing second step~third step in all individuals of population.
6. the station track metro depot Hui Ku according to claim 4 arrangement method, which is characterized in that step (4.1) is described
Determine constraint condition, wherein constraint condition includes the constraint of time interval constraint and metro depot service ability, in which:
Time interval is constrained, there are two types of situations altogether:
Situation a, first train elder generation Hui Ku are parked in A-share progress daily test operation, and operation is adjusted to B strands after the completion, and A-share empties subsequent
Second train of continued access, during first train entirely picks up, daily test time-consuming 40min, shunt time-consuming 30min, therefore first
It is more than or equal to 70min with the library time interval of returning of second train；When returning library time interval and being less than 70min, B strands of vehicles
Daily test task is unable to complete, and is directly stopped to B strands；
Situation b, first train first pass through washing track and dock to A-share progress daily test operation from dextrad, and B is adjusted to after the completion of operation
Stock, A-share empties second train of subsequent continued access, during first train entirely picks up, carwash time-consuming 15min, and daily test consumption
When 40min, shunt time-consuming 30min, therefore the library time interval of returning of first and second train is more than or equal to 85min；When first
It when returning library time interval and being less than 85min and be greater than 70min, abandons carwash task with second train and only carries out daily test；When
When time library time interval of first and second train is less than 70min, abandons daily test task and only carry out carwash；
Constraint for metro depot service ability, the same time shunts number of tasks no more than 1, and same time daily test vehicle
Number be not more than 3, it may be assumed that
Wherein, NdiFor the vehicle number of same time daily test；NdcFor the number of tasks of shunting of same time.
7. the station track metro depot Hui Ku according to claim 4 arrangement method, which is characterized in that step (4.2) is described
Determine objective function: optimization aim is task completeness highest, and the process that picks up always is shunt, and number is minimum, and vehicle goes out is put in storage convenient journey
Highest is spent, wherein task completeness highest has the first importance, and number of shunting at least has the second importance, and it is convenient to be put in storage out
Degree highest has third importance；For target zj(j=1,2,3) priority reached and each target need son to be achieved
The expression formula of target, objective function is as follows:
Wherein, lexmin, which is represented, minimizes target according to lexicographic order；m0Represent sub-goal quantity；Representing i-th of target is more than
Expected overgauge variable；I-th of target is represented more than expected minus deviation variable；Representative is distributed toPositive weights；Representative is distributed toNegative weight；
For task completeness highest, if objective function is z1, z1Have 4 sub-goals: daily test completion rate of the plan highest, vehicle stop
It puts station track type and its operation station track requires matching degree highest, carwash completion rate of the plan highest, morning peak station track to require matching degree
Highest, the highest objective function z of task completeness1Are as follows:
Wherein, TiuFor the unfinished number of tasks of i-th of sub-goal；X is penalty coefficient；For the negative power for distributing to each sub-goal
Weight；
It is minimum for number of shunting, if objective function is z2, two strands of A, B and if only if same station track are both needed to park to Hui Ku
Vehicle and B strands of vehicles need and can daily test when, need to carry out shunting service, the least objective function z of number of shunting2Are as follows:
z2=Tdc
Wherein, TdcFor number of actually shunting；
For going out storage convenience highest, if objective function is z3, z3Have 2 sub-goals: storage is additional time-consuming minimum and goes out
Library is additional time-consuming minimum, is put in storage the highest objective function z of convenience out3Are as follows:
z3=Trk+Tck
Wherein, TrcFor time-consuming number outside storage total value；TckFor number time-consuming outside outbound total value；
In conclusion the catalogue scalar functions I of the station track Hui Ku Arrangement Problem are as follows:
Work as z1=0, z2=0, z3When=0, it is required optimal solution that station track corresponding to I, which arranges scheme,.
8. the station track metro depot Hui Ku according to claim 4 arrangement method, which is characterized in that step (4.3) is described
Determine fitness function, comprising the following steps:
Step 1: calculating target value, there are 3 objective functions for each individual, i.e.,
Step 2: being ranked up according to the first priority target functional value to individual；If certain individual targets having the same
Functional value is then compared the second priority target function, and so on；If certain individuals can not finally sort, with
Machine sequence；Individual is arranged according to the raised sequence of target function value in this way；
Step 3: being each individual xkThe adaptive value based on sequence is distributed, if rkIt is individual xkPut in order, given according to user
It is as follows that a fixed parameter a ∈ (0,1) defines the adaptation value function based on sequence:
。
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| CN102248956A (en) * | 2010-05-17 | 2011-11-23 | 北京交通大学 | Networked train operation plan regulating method |
| CN103177292A (en) * | 2011-12-21 | 2013-06-26 | 重庆金美通信有限责任公司 | Metro crew working scheduling algorithm based on hybrid genetic algorithm |
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| CN103177292A (en) * | 2011-12-21 | 2013-06-26 | 重庆金美通信有限责任公司 | Metro crew working scheduling algorithm based on hybrid genetic algorithm |
| CN103192855A (en) * | 2013-03-25 | 2013-07-10 | 北京交通大学 | Method and system for adjusting train working diagrams on basis of platform redundancy |
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