CN1410911A - Calculation method for transportation vehicle controlled dispatch - Google Patents
Calculation method for transportation vehicle controlled dispatch Download PDFInfo
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- CN1410911A CN1410911A CN 01142279 CN01142279A CN1410911A CN 1410911 A CN1410911 A CN 1410911A CN 01142279 CN01142279 CN 01142279 CN 01142279 A CN01142279 A CN 01142279A CN 1410911 A CN1410911 A CN 1410911A
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Abstract
The invented component generates the optimized schedule table for dispatching the conveyance based on the genetic algorithm started in multiple running threads to look for the targets with the preset restrictions being satisfied. First, the invented component generates the multiple initial samples of two-dimensional the dispatching coding table of transport tools at random. The dispatching coding table of the transportation and the transportation service are relevant to the chromosome and gene in the genetic algorithm. The previous sample is as the sample is the parental generation. Based on the defined target function and the restriction formula, the sample evaluation is carried out. The turntable algorithm makes the sample with high evaluated value have more chance to be selected.
Description
Technical field
The present invention is the relevant technical field of handling transportation vehicle controlled dispatch, refers to a kind of calculation method that is used for transportation vehicle controlled dispatch of adopting the hereditary algorithm of two-dimensional matrix coding especially.
Background technology
Press, in the technical field of the daily operation of carrier, transport resource is meant and can be used for the appurtenance instrument that carrier carries out controlled dispatch, comprise mode and transport services group member, mode wherein comprises the means of transport of various passengers of can be used as such as sea route, land route and dead circuit or article, as: aircraft, motor bus, container ship, railway railway carriage etc., transportation is reined in the affair group member and then is divided into mode driver and passenger services person, the former makes a general reference the key personnel that the control mode is advanced, and latter's general reference is for serving the personnel of passenger or cleaning article.And the despatching work of transport resource is assigned with three parts such as assigning generation as a result and is formed by the time table of runs foundation of transportation networking, transportation networking order of classes or grades at school.Wherein, the appointment of transportation networking order of classes or grades at school is often because of the mode kind in the time table of runs, order of classes or grades at school quantity is various, causing the transportation networking order of classes or grades at school that produces the transportation vehicle controlled dispatch table to be combined into the index multiple grows up, in addition, when the transportation vehicle controlled dispatch table produces, still need and consider " mode is reorganized and outfit the time ", " identical the beginning and the end place of order of classes or grades at school continuously ", " mode do not have oiling working time ", " mode stops the fate of non-servicing center ", " the minimum duties group member meal time of the period of fixedly having a dinner ", " mode order of classes or grades at school working time ", limiting factors such as " mode scales ", show manual type and produce the transportation vehicle controlled dispatch table, then become a not only loaded down with trivial details but also inefficient job, and usually be difficult in the limited time, produce optimized transportation vehicle controlled dispatch table, and then cause company relatively poor market adaptability to changes and human resource utilization.
United States Patent (USP) 5,848, No. 403 cases are to propose a kind of " System and method for of heredity calculation scheduling " (System and method for genetic algorithm scheduling systems), can utilize hereditary algorithm to carry out the controlled dispatch of resource, precisely because hereditary algorithm is the coded system of adopting one-dimensional linear or tandem, therefore the problem expressivity is relatively poor, is difficult for understanding, to find the solution efficient relatively poor.In view of this, the running of aforementioned transport resource controlled dispatch workflow and producing method as a result still have necessity of being improved.
The inventor whence originally in the spirit of positive invention, is urgently thought a kind of " calculation method that is used for transportation vehicle controlled dispatch " that can address the above problem because of in this, and several times research experiment is eventually to finishing this novel progressive invention.
Summary of the invention
The objective of the invention is is providing a kind of calculation method that is used for transportation vehicle controlled dispatch, adopt the hereditary algorithm of two-dimensional matrix formula coded system, can give full expression to the problem characteristic, produce the higher efficient of finding the solution, and reach system operation and problem solving algorithm with multi-threading and independently operate framework with concurrent development, can improve system resource utilization efficient and system development time-histories.
For reaching aforesaid purpose, the calculation method that is used for transportation vehicle controlled dispatch of the present invention is after setting mode scheduling basic document, starting with hereditary algorithm with multi-threading is the optimization transportation vehicle controlled dispatch table producing component of core, satisfy restrictive condition and the target of stipulating so that look for, this optimization transportation vehicle controlled dispatch table producing component comprises: (B1) produce a plurality of initial samples at random, each initial sample is to dispatch coding schedule for a two dimension mode that includes a plurality of transport services, mode represented in vertical index of this mode scheduling coding schedule, laterally time sequencing represented in index, and this mode scheduling coding schedule and transport services thereof are the chromosome and the gene of corresponding hereditary algorithm; (B2) be the parental generation sample with aforementioned sample,, carry out the sample assessment, to ask for its chromosomal sample assessed value according to the objective function and the restraint-type of definition; (B3) utilization wheel disc rule makes the comparatively good chromosome of assessed value increase selected chance; (B4) carry out chromosome mating and gene mutation with the selection probability of single-point patterning method and two point patterning method; (B5) carry out sample and replace, carry out because of exchanged form with local loop, according to chromosomal sample assessed value sample is sorted, and select more excellent sample, wherein, the assessed value of each sample is can violate cost by objective function and restraint-type to be determined; And (B6) reached restriction when carrying out number of times, and or the violation number of normal restraint-type is when being zero, the variation of its sample assessed value then finishes to carry out within a preset value time, otherwise, be the parental generation sample with the sample that is obtained, execution in step (B2) is to (B5) again.
In step (B3), be to give the different probability that is selected respectively wherein according to each chromosomal assessed value size.
Wherein in step (B4), the chromosome mating is the method with the gene group exchange, produces the filial generation sample in conjunction with the parent excellent genes.
When carrying out the chromosome mating, be wherein with vertical direction cutting chromosome.
Wherein when carrying out the chromosome mating,, then adopt the two point patterning method to carry out the chromosome mating, if not, then adopt the single-point patterning method to carry out the chromosome mating if selected probability is put predefined probability greatly.
Wherein in step (B4), gene mutation is the method with local gene swapping, makes sample can have diversity, and the search space of enlarged sample is avoided being absorbed in local optimum and separated.
Wherein when carrying out gene mutation, if selected probability, is then selected time of desiring to carry out gene mutation at first at random greater than predefined probability, secondly then seek the transport resource that can carry out gene mutation, two transport resources that also should the time exchange.
Wherein also comprise a step mule (C) to export an optimization transport resource controlled dispatch table.
Wherein this restrictive condition comprises: mode is reorganized and outfit time, mode does not have the non-servicing center time that stops the working time of oiling, mode, transport services group member meal time, and mode order of classes or grades at school working time.
Wherein restraint-type violation cost is to violate the project sum of each restraint-type and the product of corresponding penalty value for chromosome.
Wherein objective function comprises identical the beginning and the end place of mode utilization ratio and continuous order of classes or grades at school.
Wherein chromosomal sample assessed value is:
SCORE=Cost_FIFO+Cost_ModDispatch+Penalty_Cons, in the middle of, Cost_FIFO is that order of classes or grades at school is connected excessive cost incurred of T.T., and Cost_ModDispatch is a mode scheduling cost, and Penalty_Cons is that restraint-type is violated cost.
Wherein Penalty_Cons is zero.
Because modern design of the present invention can provide on the industry and utilize, and truly have the enhancement effect, so apply for a patent in accordance with the law.
Description of drawings
For making the auditor can further understand structure of the present invention, feature and purpose thereof, below in conjunction with the detailed description of accompanying drawing and preferred embodiment as after, wherein:
Fig. 1 is the applied system architecture diagram of calculation method that is used for transportation vehicle controlled dispatch of the present invention.
Fig. 2 is the operational flowchart for a transportation vehicle controlled dispatch system.
Fig. 3 is an optimization transportation vehicle controlled dispatch table producing component process flow diagram.
Fig. 4 A dispatches coding schedule for a two dimension mode that includes a plurality of transport services.
Fig. 4 B is an example of dispatching coding schedule for a mode that includes four transport services.
Fig. 5 carries out the synoptic diagram that sample is eliminated for one with the wheel disc rule.
Fig. 6 is for carrying out the synoptic diagram of chromosome mating.
Fig. 7 is for carrying out the synoptic diagram of gene mutation.
Embodiment
The relevant preferred embodiment that is used for the calculation method of transportation vehicle controlled dispatch of the present invention, please be earlier with reference to system architecture diagram shown in Figure 1, it is to use the data access framework of client/servo (client/Server), with the relevant transportation vehicle controlled dispatch data of access, wherein, the user of client 11 sees through the networking, asks for the transportation vehicle controlled dispatch table that is stored in its end to server-side 12 and produces related data.
And please refer to shown in the transportation vehicle controlled dispatch system operation process flow diagram of Fig. 2, client 11 is to see through the system operation interface to finish the relevant basic data setting of mode scheduling, and via the decipher of File Format, method startup with multi-threading (multi-thread) is the optimization transportation vehicle controlled dispatch table producing component of core with hereditary algorithm (GeneticAlgorithm), after looking for the satisfied restriction of stipulating and target, so that produce the optimization transportation vehicle controlled dispatch table that exports general computer outputs to.
Fig. 3 further shows aforementioned optimization transportation vehicle controlled dispatch table producing component process flow diagram, it at first need produce a plurality of initial samples (step S301) at random, each initial sample is for just like the two dimension mode scheduling coding schedule that includes a plurality of transport services 41 shown in Fig. 4 A, wherein, and vertical index p
1..., P
αRepresent mode 1 respectively ..., mode α, laterally index d
1..., d
β Represent time sequencing 1 respectively ..., time sequencing β, coding tabular value ω
α βRepresent the transport services code name.For example, suppose that mode is an aircraft, and flight board is:
| The order of classes or grades at school code name | The departure time | Landing time | The original base code name | The original base code name | Flight time |
| ????812 | ????1010 | ????1100 | ??7 | ??17 | ????50 |
| ????813 | ????1020 | ????1110 | ??17 | ??7 | ????50 |
| ????822 | ????1430 | ????1520 | ??7 | ??17 | ????50 |
| ????838 | ????2100 | ????2150 | ??7 | ??17 | ????50 |
Then its sample can be the mode scheduling coding schedule that includes four transport services shown in Fig. 4 B.Aforementioned again mode scheduling coding schedule is a chromosome of corresponding hereditary algorithm, and each transport services of mode scheduling coding schedule then is equivalent to a gene.
By the first generation sample of output at random immediately as parental generation sample (step S302), this sample obviously can't satisfy the objective function and the restraint-type definition (step S303) of all settings, (step S304) its chromosome assessed value (Fitness value) good and bad widely different as can be known in sample assessment, so can use wheel disc rule (roulette wheel) to make the comparatively good chromosome of assessed value increase selected chance, so that eliminate bad sample, and please refer to and shown in Figure 5ly carry out the synoptic diagram that sample is eliminated with the wheel disc rule, among the figure 1 ... P is P the probability that sample was selected, the wheel disc rule is to give the different probability that is selected respectively according to each chromosomal assessed value size, so, can set the comparatively good sample of assessed value bigger selected chance is arranged, also though the reserve part assessed value is relatively poor simultaneously, but the good sample of local chromosome possibility has the improved chance of continuation for assessed value.
Step S305 carries out chromosome mating and gene mutation again, and wherein, chromosome mating (Crossover) is the method with the gene group exchange, produces the filial generation sample in conjunction with the parent excellent genes, makes the sample in each generation develop and can become better and better.Because the quantity and the content of transport services every day promptly can not change after generation, and be correct in order to ensure transport services every day quantity and content, when carrying out the chromosome mating, be therefore with vertical direction cutting chromosome, as shown in Figure 6.When carrying out the chromosome mating,, if not, then adopt single-point cutting to carry out the chromosome mating if selected probability greater than predefined probability, then adopts two point cutting to carry out the chromosome mating.
And gene mutation (Mutation) is the method with local gene swapping, makes sample can have diversity, and the search space of enlarged sample is avoided being absorbed in local optimum and separated.As homologous chromosomes mating method, also need guarantee during gene mutation that transport services quantity and the content of every day is correct, so sudden change the time also only limits to transport services exchange on the same day.If selected probability is greater than predefined probability, then select time of desiring to carry out gene mutation at first at random, secondly then seek the mode that can carry out gene mutation, two modes that also should the time exchange, and if not, then do not carry out gene mutation.Its gene mutation method as shown in Figure 7.
After the step of dyed body exchange and gene mutation, carry out sample again and replace (step S306), sample is sorted according to chromosomal assessed value, and select more excellent sample (for example for the lower sample of assessed value), wherein, the assessed value of each sample (Score) is to be obtained by the target function value combination.For example, objective function is divided into two parts, one is the equalization degree with the fairness index of minimizing of operation costs, and another is the not satisfaction degree of each restraint-type, and wherein, with mode, its relevant restrictive condition is:
1. mode is reorganized and outfit the time: cleaning mode or inspection mode upstate required time between order of classes or grades at school and order of classes or grades at school;
2. mode does not have oiling working time (mode cruise time): the total run time when mode need not increase fuel newly;
3. mode stops the non-servicing center time (the mode service time at interval): mode must be accepted the time interval of all kinds of maintenances;
4. transport services group member meal time: provide one section of transport services group member fixing have a dinner during; And
5. mode order of classes or grades at school working time: mode is by starting point working time to terminal in the timetable.
And chromosome is violated the project sum of each restraint-type and the product of corresponding penalty value, is restraint-type and violates cost, and its restraint-type of feasible solution is violated the punishment cost and be should be zero.Can be expressed as follows with mathematical expression,
Penaty_Cons＝PConsModTurnArround*NConsModTurnArround
+PConsModCruise*NConsModCruisel
+PConsModMaintain*NConsModMaintain
+PConsMealTm*NConsMealTm
+PConsTripTm*NConsTripTm
Wherein, PconsModTumArround is that desire reduces the restraint-type penalty value that the violation mode is reorganized and outfit time restriction; NConsModTumArround is for all violate the sum that mode is reorganized and outfit time restriction in certain sample; PconsModCruise is that desire reduces the restraint-type penalty value of violating the mode cruise time; NConsModCruise is the sum of all mode cruise time restrictions in certain sample; PConsModMaintain is that desire reduces violation mode service time interval constraint formula penalty value; NconsModMaintain is all sums of violating mode service time interval constraint in certain sample; PConsMealTm is that desire reduces the restraint-type penalty value of violating transport services group member's meal time; NConsMealTm is the sum that all violation transport services group member's meal times limit in certain sample; PConsTripTm is that desire reduces the violation mode order of classes or grades at school restraint-type penalty value of working time; NConsTripTm is all sums of violating restriction working time of mode order of classes or grades at school in certain sample.
The operation costs of mode and fairness index class comprise again:
1. mode utilization ratio (FIFO assessment): the phase minimizes the summation of order of classes or grades at school convergence time, is expressed as
Wherein, Cost_FIFO is that order of classes or grades at school is connected excessive cost incurred of T.T.; TmTurnAroun d
I, i+1Be the time interval between i and i+1, W
TmTumArroundFor desire reduces the weight that order of classes or grades at school is connected the T.T. phenomenon.
2. continuous identical the beginning and the end place (mode scheduling cost) of order of classes or grades at school: the starting point coherence request of the terminal point of preceding order of classes or grades at school and this order of classes or grades at school is expressed as
Wherein, NConnect
I, i+1For taking place, order of classes or grades at school is connected the different number in place; W
ConnectReduce the weight of mode scheduling cost for desire.
Therefore, chromosomal objective function comprises mainly that airliner utilization ratio maximization and restraint-type are violated and punishes cost, can the following formula table it:
SCORE＝Cost_FIFO+Cost_ModDispatch+Penalty_Cons，
As the chromosome with Fig. 4 B is example, reorganizes and outfit time restriction and mode scheduling cost if only consider mode, and:
PconModTurnAround＝50
W
Connect=100:
Score＝Penalty_Cons+Cost_ModDispatch
＝(1+0)×50+(0+1)×100
Reorganize and outfit time restriction so 812 and 813 violate mode, 822 and 838 landing places are inconsistent, cause mode scheduling cost to increase.The sample assessed value of a right feasible solution only comprises that mode scrapes the rate degree of using., as shown in the formula:
SCORE＝Cost_FIFO+Cost_ModDispatch。
Therefore, as long as check whether the violation number of restraint-type is zero, knows promptly whether it is separated is feasible solution.The termination condition of whole algorithm can be the restriction of total execution algebraically or when the violation number of restraint-type when being zero, the variation of its sample assessed value within 0.001, as shown in the formula,
|SCORE
g-SCORE
g-1|/SCORE
g-1＜0.001
Wherein, SCORE
gWith SCORE
G-1Be respectively violation number when restraint-type when being zero, this and the sample assessed value of computing last time.Otherwise, as do not meet termination condition, and be the parental generation sample then with the sample that is obtained, execution in step S302 to S306 so repeats up to meeting termination condition again, can obtain optimized result.
By above explanation as can be known, hereditary algorithm of the present invention is adopted two-dimensional matrix formula coded system, can give full expression to the problem characteristic, produce the higher efficient of separating, and reach system operation and problem solving with multi-threading and drill fine and soft method and independently operate framework with concurrent development, improve system resource utilization efficient and system development time-histories.
In sum, no matter the present invention is all showing it totally different in the feature of known techniques with regard to purpose, means and effect, in fact is one to have the invention of practical value.Only it should be noted that above-mentioned many embodiment give an example for convenience of explanation, the interest field that the present invention advocated should be as the criterion so that claim is described certainly, but not only limits to the foregoing description.
Claims (13)
1. a calculation method that is used for transportation vehicle controlled dispatch is characterized in that, mainly comprises following step:
(A) set mode scheduling basic document; And
(B) starting with hereditary algorithm with multi-threading is the optimization transportation vehicle controlled dispatch table producing component of core, satisfies restrictive condition and the target of stipulating so that look for, and it comprises step:
(B1) produce a plurality of initial samples at random, each initial sample is to dispatch coding schedule for a two dimension mode that includes a plurality of transport services, mode represented in vertical index of this mode scheduling coding schedule, laterally time sequencing represented in index, and this mode scheduling coding schedule and transport services thereof are the chromosome and the gene of corresponding hereditary algorithm;
(B2) be the parental generation sample with aforementioned sample,, carry out the sample assessment, to ask for its chromosomal sample assessed value according to the objective function and the restraint-type of definition;
(B3) utilization wheel disc rule makes the comparatively good chromosome of assessed value increase selected chance;
(B4) carry out chromosome mating and gene mutation with the selection probability of single-point patterning method and two point patterning method;
(B5) carry out sample and replace, carry out because of exchanged form with local loop, according to chromosomal sample assessed value sample is sorted, and select more excellent sample, wherein, the assessed value of each sample is can violate cost by objective function and restraint-type to be determined: and
(B6) reached restriction when carrying out number of times, or when the violation number of restraint-type is zero, the variation of its sample assessed value then finishes execution within a preset value time, otherwise, be the parental generation sample with the sample that is obtained, execution in step (B2) is to (B5) again.
2. the calculation method that is used for transportation vehicle controlled dispatch as claimed in claim 1 is characterized in that, in step (B3), is to give the different probability that is selected respectively according to each chromosomal assessed value size wherein.
3. the calculation method that is used for transportation vehicle controlled dispatch as claimed in claim 1 is characterized in that, wherein in step (B4), the chromosome mating is the method with the gene group exchange, produces the filial generation sample in conjunction with the parent excellent genes.
4. the calculation method that is used for transportation vehicle controlled dispatch as claimed in claim 3 is characterized in that, when carrying out the chromosome mating, is with vertical direction cutting chromosome wherein.
5. the calculation method that is used for transportation vehicle controlled dispatch as claimed in claim 4, it is characterized in that, wherein when carrying out the chromosome mating, if selected probability is put predefined probability greatly, then adopt the two point patterning method to carry out the chromosome mating, if not, then adopt the single-point patterning method to carry out the chromosome mating.
6. the calculation method that is used for transportation vehicle controlled dispatch as claimed in claim 1 is characterized in that, wherein in step (B4), gene mutation is the method with local gene swapping, make sample can have diversity, the search space of enlarged sample is avoided being absorbed in local optimum and is separated.
7. the calculation method that is used for transportation vehicle controlled dispatch as claimed in claim 6, it is characterized in that, wherein when carrying out gene mutation, if selected probability is greater than predefined probability, then select the time desire to carry out gene mutation at first at random, secondly then seek the transport resource that can carry out gene mutation, two transport resources that also should the time exchange.
8. the calculation method that is used for transportation vehicle controlled dispatch as claimed in claim 1 is characterized in that, wherein also comprises a step mule (C) to export an optimization transport resource controlled dispatch table.
9. the calculation method that is used for transportation vehicle controlled dispatch as claimed in claim 1, it is characterized in that wherein this restrictive condition comprises: mode is reorganized and outfit time, mode does not have the non-servicing center time that stops the working time of oiling, mode, transport services group member meal time, and mode order of classes or grades at school working time.
10. the calculation method that is used for transportation vehicle controlled dispatch as claimed in claim 9 is characterized in that, wherein restraint-type violation cost is to violate the project sum of each restraint-type and the product of corresponding penalty value for chromosome.
11. the calculation method that is used for transportation vehicle controlled dispatch as claimed in claim 9 is characterized in that, wherein objective function comprises identical the beginning and the end place of mode utilization ratio and continuous order of classes or grades at school.
12. the calculation method that is used for transportation vehicle controlled dispatch as claimed in claim 11 is characterized in that, wherein chromosomal sample assessed value is:
SCORE＝Cost_FIFO+Cost_ModDispatch+Penalty_Cons，
In the middle of, Cost_FIFO is that order of classes or grades at school is connected excessive cost incurred of T.T., and Cost_ModDispatch is a mode scheduling cost, and Penalty_Cons is that restraint-type is violated cost.
13. the calculation method that is used for transportation vehicle controlled dispatch as claimed in claim 12 is characterized in that, wherein Penalty_Cons is zero.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101520890B (en) * | 2008-12-31 | 2011-04-20 | 广东威创视讯科技股份有限公司 | Grey scale characteristic graph-based automatic separation method for conglutinated chromosomes |
| CN110322016A (en) * | 2018-03-28 | 2019-10-11 | 中华电信股份有限公司 | Analysis server apparatus and its optimal combination analysis method |
| TWI799835B (en) * | 2021-04-16 | 2023-04-21 | 兆豐國際商業銀行股份有限公司 | Electronic device and method of assigning service bank branch for store |
-
2001
- 2001-09-26 CN CN 01142279 patent/CN1410911A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101520890B (en) * | 2008-12-31 | 2011-04-20 | 广东威创视讯科技股份有限公司 | Grey scale characteristic graph-based automatic separation method for conglutinated chromosomes |
| CN110322016A (en) * | 2018-03-28 | 2019-10-11 | 中华电信股份有限公司 | Analysis server apparatus and its optimal combination analysis method |
| TWI799835B (en) * | 2021-04-16 | 2023-04-21 | 兆豐國際商業銀行股份有限公司 | Electronic device and method of assigning service bank branch for store |
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