CN101261702A - A schedule scheme evaluation and selection method based on hierarchical optimization - Google Patents
A schedule scheme evaluation and selection method based on hierarchical optimization Download PDFInfo
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- CN101261702A CN101261702A CNA2008100357738A CN200810035773A CN101261702A CN 101261702 A CN101261702 A CN 101261702A CN A2008100357738 A CNA2008100357738 A CN A2008100357738A CN 200810035773 A CN200810035773 A CN 200810035773A CN 101261702 A CN101261702 A CN 101261702A
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Abstract
The invention provides a scheduling scheme evaluating and selecting method based on optimizing layer by layer. The method carries out multi-layer judging on the obtained scheduling schemes to realize multi-goal optimizing by adopting the thought of optimizing layer by layer, namely according to the restricting conditions, a main optimizing goal and a secondary optimizing goal, evaluates the obtained scheduling schemes through the restricting conditions and calculating the fitness during the evaluating process and finally outputs the scheduling scheme with least breach of restricting conditions as the best scheduling scheme. The scheduling scheme evaluating and selecting method of the invention realizes the multi-goal optimizing and avoids optimizing the parameters comparatively difficult to confirm such as a goal weight; furthermore, the scheduling scheme evaluating and selecting method of the invention can also select more excellent individuals of each generation to ensure the diversity of parent populations by arranging a feasible solution pool and an infeasible solution pool when selecting the parent populations, thus preparing excellent foundation for obtaining the best scheduling scheme so as to finally improve the using efficiency of enterprise manufacturing resources, reduce the cost and increase the enterprise competitive strength.
Description
Technical field
The present invention relates to a kind of evaluation and system of selection of schedule scheme, especially a kind of schedule scheme evaluation and system of selection based on hierarchical optimization.
Background technology
Genetic algorithm is a kind of direct search optimization method based on genetics and the generation of science of heredity mechanism, and it seeks best solution by selection, intersection, the variation of gene string.In recent years, this algorithm is as a kind of general optimized Algorithm, because of its coding techniques and genetic manipulation is fairly simple, optimize unrestricted condition constraint, especially have computation capability and overall solution space search capability, be applied in all trades and professions widely.The production scheduling problem---promptly how rationally to utilize Limited resources to reach the productive target of expection, also can be optimized solution by this algorithm.
Solve in the process of production scheduling problem in the application genetic algorithm; usually can attach a lot of constraint conditions; the situation more complicated; how the gained schedule scheme is carried out rationally and efficiently estimating and selecting; carrying out the choosing of deleting of the survival of the fittest to getting schedule scheme, is the essential step that finally obtains the schedule scheme of high-quality and high-efficiency.
Summary of the invention
The purpose of this invention is to provide a kind of schedule scheme evaluation and system of selection based on hierarchical optimization, under the constraint condition and optimization aim that provides based on the user for schedule scheme, to schedule scheme is estimated, is optimized and finally selects optimum implementation.
The method adopts the thought of hierarchical optimization, promptly carry out multilayer judge realization multiple-objection optimization to getting schedule scheme according to constraint condition, main optimization aim, suboptimization target, and in evaluation procedure, to getting schedule scheme, calculate by constraint condition inspection, fitness, estimate, final output is violated the minimum schedule scheme of constraint condition as optimum schedule scheme, the method that makes has avoided not having the situation of separating, for the user in the subsequent operation process, schedule scheme adjustment is laid the foundation, and concrete steps are as follows:
There is different processing technologys in different factories, and the constraint condition that causes needs to be considered has nothing in common with each other, even sometimes constraint condition is identical, factory is also different to the attention degree of each constraint condition.When constraint condition was too much, algorithm may cause obtaining feasible solution, need give up the unessential constraint condition of part.This just makes in the production scheduling system, and constraint condition also has the character of the optimization aim of being similar to, even the optimization aim stronger than optimization aim when we can say.Therefore the user must be provided with priority to the constraint condition that needs are considered, promptly provides the preference relation of constraint condition.So,
1. main optimization aim, suboptimization target and constraint condition and importance degree grade thereof are set;
2. schedule scheme is carried out the constraint condition check: to satisfying the schedule scheme of constraint condition, promptly feasible solution is carried out fitness by main optimization aim and is calculated; To not satisfying the schedule scheme of constraint condition, promptly infeasible solution carries out fitness by constraint condition and calculates;
3. two the elite Xie Chi in feasible solution pond and infeasible solution pond are set, press the fitness size and keep excellent individual;
4. to the schedule scheme in feasible solution pond and the infeasible solution pond, according to main optimization aim and suboptimization target pass judgment on, hierarchical optimization;
5. export optimum schedule scheme.
The importance degree grade of the constraint condition in the described step 1 is higher than described main optimization aim and suboptimization target.
Constraint condition in the described step 1 is divided into order level or worker's single-stage or operation level.
Constraint condition in the described step 1, each bar constraint condition has the constraint condition checking information table of a correspondence, comprises field: code constraint and/or constraint-prioritized level and/or constrained type and/or order number, worker's odd numbers and/or operation number and/or constraint flag information and/or retrain good and bad information.
The check of constraint condition in the described step 2 is that by whether schedule scheme satisfies that all constraint conditions test in the information table each is judged.
Being undertaken in the fitness calculating in the described step 2 by main optimization aim, the design of fitness function is professional meaning and the mathematical meaning according to optimization aim, expression can be measured the form of schedule scheme.
Carrying out fitness by constraint condition and calculate in the described step 2 is the weighted sum of calculating the constraint condition that schedule scheme satisfied, and constraint condition all has different weights according to the significance level difference here, to the fitness value of infeasible schedule scheme X is
ω
iBe the weights of i class constraint condition, F
iBe the number that satisfies of i class constraint condition, N is the class number of constraint condition.
Separating that but Xie Chi and intangibility pond can be stored in the described step 3 is limited.
But separating by the size of fitness in Xie Chi and the intangibility pond deposited successively in the described step 3.
In the described step 4 according to main optimization aim and suboptimization target pass judgment on, hierarchical optimization, separate with the feasible solution pond in branch feasible solution pond does not have the two kinds of situations of separating.When separate in the feasible solution pond, its process may further comprise the steps: i. is for separating in the feasible solution pond, press the fitness height, select the less a collection of individuality of diversity factor of fitness value, individual number satisfies the qualification of proportion threshold value, ii. based on this batch individuality, select an individuality that satisfies the suboptimization target most as optimum schedule scheme; Do not have when the feasible solution pond and to separate, its process may further comprise the steps: i. is for separating in the infeasible solution pond, press the fitness height, select the less a collection of individuality of diversity factor of fitness value, individual number satisfies the qualification of proportion threshold value, ii. based on this batch individuality, select an individuality that satisfies main optimization aim most as optimum schedule scheme.
When the inventive method is carried out schedule scheme evaluation and selected,, and under the situation of needs, select infeasible solution also as a reference scheme.This is because infeasible solution has following meaning in production scheduling: one, proceed from reality, infeasible solution does not promptly satisfy the schedule scheme of constraint condition, some constraint condition does not satisfy, and as order constraint at delivery date, can make constraint condition satisfy again by the negotiation with the client.So infeasible solution is not absolute " infeasible ".Two, by the scheduling process is made interactive operation, suitably adjust the input information that schedule scheme or minimal change scheduling are calculated, infeasible solution can become feasible solution sometimes.Three, because the production scheduling solution space is irregular discrete space, sometimes be difficult to obtain feasible solution, so when the degree of the illegal constraint of infeasible solution is not too strong, as operations such as the intersection of parent by genetic algorithm, variations, still might produce feasible offspring individual, make genetic algorithm stable operation.Though four, infeasible solution means that certain several workers' list does not satisfy constraint condition, after these several workers single " artificially " were excluded, the scheduling plan of remaining worker's list also had meaning.
The invention has the beneficial effects as follows provides a kind of schedule scheme evaluation and system of selection based on hierarchical optimization, realized multiple-objection optimization, and when a plurality of optimization aim are conflicted mutually, can be under the prerequisite of the main optimization aim of absolute assurance, be optimized at the suboptimization target, avoided more doubt parameters such as optimization aim weight; Also, make, can choose the successive dynasties, avoid excellent individual to lose, can ensure the diversity of parent population simultaneously again, prevent to be absorbed in local optimum than excellent individual selecting parent kind group time by feasible solution pond and infeasible solution pond are set.Thereby, have laid a good foundation for obtaining an optimization schedule scheme, with the final service efficiency that improves enterprise's resources of production, reduced cost, increased Enterprises'Competitiveness.
Description of drawings
Fig. 1 is a constraint condition checking information table.
Fig. 2 is the evaluation of hierarchical optimization schedule scheme and selects process flow diagram.
Fig. 3 is that the hierarchy optimization mode realizes the multiple-objection optimization process flow diagram.
Embodiment
The present invention is further described below in conjunction with drawings and Examples.
In the present embodiment, related optimization aim comprises:
1. punctual delivery guarantees as far as possible that promptly product completed on time before near delivery date.
2. minimum completion date promptly requires the single completion as early as possible of worker of all processing.
3. minimum flow process time workpiece promptly begins to be worked into its intact man-hour after reaching the spot, its time that is spent in system minimizes.
4. minimum Workshop Production cost mainly comprises product consumption of raw material expense, cost of labor expense, manufacturing expense and managerial cost etc.
5. minimize and produce setup time.
6. maximization plant factor.
7. the order pre-empt resources that priority is high.
A kind of schedule scheme evaluation and system of selection based on hierarchical optimization may further comprise the steps:
1. the importance degree grade of main optimization aim, suboptimization target and constraint condition is set;
A., main optimization aim is set:
Select a kind of optimization aim as main optimization aim in the multiple optimization aim that the user can provide more than system, or oneself redefine main optimization aim.
B., the suboptimization target is set:
The suboptimization target is to determine to select remaining optimization aim as required on the basis of main optimization aim, and to the suboptimization target according to ordering of optimization preference.
C., constraint condition is set:
To conditional test information table of each bar constraint condition setting, content sees also Fig. 1, i.e. the constraint condition checking information table of present embodiment.Constraint condition checking information table comprises code constraint, constraint-prioritized level, constrained type, fields such as order number, worker's odd numbers, operation number, constraint flag information, the good and bad information of constraint.Wherein, constrained type is divided into:
A) order level constraint is as constraint at delivery date, the longest line duration constraint of order, the shortest line duration constraint of order etc.
B) constraint of worker's single-stage is as the single constraint constantly that goes into operation the earliest of worker, the single constraint constantly that goes into operation the latest of worker, the single completion the earliest of worker constraint constantly, the single completion the latest of worker constraint constantly, worker's the longest single line duration constraint, worker's the shortest single line duration constraint etc.
C) constraint of operation level, as current time constraint, constraint constantly, operation maximum time spacing constraint, minimum process retrain in batches, the materiel warehouse-in phase retrains to specify go into operation constantly constraint, operation to complete the latest.
2. schedule scheme is carried out constraint condition check and evaluation, flow process sees also Fig. 2, and concrete steps are as follows
A. schedule scheme constraint test:
Whether each schedule scheme passes through the check of all constraint information tables, compare with regard to each to meet, and after the judgement, corresponding flag information is carried out assignment.
If do not satisfy constraint condition, its flag information order is for-1, otherwise order is 1.Retrain good and bad information for violating the degree of this constraint: for example certain worker has singly failed to come out on time three days, and then the single flag information of this worker is-1 in the constraint condition checking information table at delivery date, good and bad information be 3 (my god).
B. judge whether schedule scheme satisfies all constraint conditions, whether all in promptly constraint condition checking information tables, flag information all is 1: if continue step c; Otherwise, continue steps d.
C. this schedule scheme satisfies all constraint conditions, is feasible solution, carries out fitness according to optimization aim and calculates, the output fitness value.The schedule scheme check finishes with evaluation.
Different optimization aim, the fitness function difference.Fitness value is big more, and it is good more to represent that then schedule scheme satisfies the degree of optimization aim.With the punctual delivery is example, and the fitness function of schedule scheme X is
Function Ln (x) is to be the logarithmic function at the end with the exponent e, T
j DueBe the delivery date of order j, t
j EndBe the order j plan completion moment, Δ (0.04) is a parameter.
D. this schedule scheme does not satisfy constraint condition, and promptly in the constraint condition checking information table, it is-1 that flag information is arranged, and then this schedule scheme is an infeasible solution.Carry out fitness calculating carrying out fitness by constraint condition and calculate the output fitness value.The schedule scheme check finishes with evaluation.
The fitness computing is as follows: ask the weighted sum of the satisfied constraint condition of schedule scheme, constraint condition all has different weights according to the significance level difference here, and the fitness value of then infeasible schedule scheme X is
ω
iBe the weights of i class constraint condition, F
iBe the number that satisfies of i class constraint condition, N is the class number of constraint condition.
3. two the elite Xie Chi in feasible solution pond and infeasible solution pond are set, and keep excellent individual by the fitness size: feasible solution and infeasible solution that step 2 is judged deposit corresponding feasible solution pond and infeasible solution pond in successively by the fitness size.The individuality of storing in separating the pond has reached maximum-norm, and last individuality in the pond (gene string and pairing schedule scheme thereof) is separated in deletion.
4. select the highest schedule scheme of fitness value in the schedule scheme from feasible solution pond and infeasible solution pond, flow process sees also Fig. 3, and concrete steps are as follows:
A., MAXIMUM SELECTION proportion threshold value L is set.Proportion threshold value is to select individuality to account for the upper limit of the ratio of the individual sum in feasible solution pond (infeasible solution) in the feasible solution pond (infeasible solution pond).
B. judge whether the feasible solution pond is empty: in this way, continue next step c; Otherwise, execution in step f.
C. adopt statistical method,, calculate the diversity factor of ideal adaptation degree value in the feasible solution pond by calculating the variance of all fitness values of separating in the feasible solution pond;
D. for separating in the feasible solution pond, press the fitness height, select the less a collection of individuality of diversity factor of fitness value, individual number satisfies the qualification of proportion threshold value.
For main optimization aim, selected this batch individuality is to separate a collection of individuality best in the pond, and almost is of equal value.
E. based on this batch individuality, select an individuality that satisfies the suboptimization target most as optimum schedule scheme, step 4 finishes.
F. adopt statistical method,, calculate the diversity factor of ideal adaptation degree value in the infeasible solution pond by calculating the variance of all fitness values of separating in the feasible solution pond;
G. for separating in the infeasible solution pond, press the fitness height, select the less a collection of individuality of diversity factor of fitness value, individual number satisfies the qualification of proportion threshold value.
For constraint condition, selected this batch individuality is that Xie Chizhong satisfies the best and close a collection of individuality of constraint condition.
H. based on this batch individuality, select an individuality that satisfies main optimization aim most as optimum schedule scheme.
For schedule scheme, when the degree that does not satisfy constraint hour, its part schedule scheme that satisfies constraint still can be adopted by the user, has avoided not having the generation of the situation of separating, and in actual applications, will do further to adjust to ungratified part.
5. export optimum schedule scheme.
Only for the preferred embodiment of invention, be not to be used for limiting practical range of the present invention in sum.Be that all equivalences of doing according to the content of the present patent application claim change and modification, all should be technology category of the present invention.
Claims (13)
1. schedule scheme evaluation and system of selection based on a hierarchical optimization is characterized in that said method comprising the steps of:
1. main optimization aim, suboptimization target and constraint condition and importance degree grade thereof are set;
2. schedule scheme is carried out the constraint condition check: to satisfying the schedule scheme of constraint condition, promptly feasible solution is carried out fitness by main optimization aim and is calculated; To not satisfying the schedule scheme of constraint condition, promptly infeasible solution carries out fitness by constraint condition and calculates;
3. two the elite Xie Chi in feasible solution pond and infeasible solution pond are set, press the fitness size and keep excellent individual;
4. to the schedule scheme in feasible solution pond and the infeasible solution pond, according to main optimization aim and suboptimization target pass judgment on, hierarchical optimization;
5. export optimum schedule scheme.
2. a kind of schedule scheme evaluation and system of selection based on hierarchical optimization according to claim 1 is characterized in that:
The importance degree grade of the constraint condition of described step in 1. is higher than described main optimization aim and suboptimization target.
3. a kind of schedule scheme evaluation and system of selection based on hierarchical optimization according to claim 1 is characterized in that:
The constraint condition of described step in 1. is divided into order level or worker's single-stage or operation level.
4. a kind of schedule scheme evaluation and system of selection based on hierarchical optimization according to claim 1 is characterized in that:
The constraint condition of described step in 1., each bar constraint condition has the constraint condition checking information table of a correspondence, comprises field: code constraint and/or constraint-prioritized level and/or constrained type and/or order number, worker's odd numbers and/or operation number and/or constraint flag information and/or retrain good and bad information.
5. according to claim 4 described a kind of schedule scheme evaluation and system of selection, it is characterized in that based on hierarchical optimization:
The constraint condition check of described step in 2. is that by whether schedule scheme satisfies that all constraint conditions test in the information table each is judged.
6. a kind of schedule scheme evaluation and system of selection based on hierarchical optimization according to claim 5 is characterized in that:
Described step being undertaken during fitness calculates in 2. by main optimization aim, the design of fitness function is professional meaning and the mathematical meaning according to optimization aim, expression can be measured the form of schedule scheme.
7. a kind of schedule scheme evaluation and system of selection based on hierarchical optimization according to claim 5 is characterized in that:
Described step carrying out fitness by constraint condition and calculate in 2. is the weighted sum of calculating the constraint condition that schedule scheme satisfied, and constraint condition all has different weights according to the significance level difference here, to the fitness value of infeasible schedule scheme X is
ω
iBe the weights of i class constraint condition, F
iBe the number that satisfies of i class constraint condition, N is the class number of constraint condition.
8. a kind of schedule scheme evaluation and system of selection based on hierarchical optimization according to claim 5 is characterized in that:
But described step 3. in separating of can storing of Xie Chi and intangibility pond be limited.
9. a kind of schedule scheme evaluation and system of selection based on hierarchical optimization according to claim 5 is characterized in that:
But described step 3. in separating in Xie Chi and the intangibility pond by the size of fitness deposit successively.
10. according to claim 1 or 6 or 7 described a kind of schedule scheme evaluation and systems of selection, it is characterized in that based on hierarchical optimization:
The schedule scheme quantity that the participation of described step in 4. passed judgment on, optimized is that the passing ratio threshold value is controlled: individuality of selecting in feasible solution pond (or infeasible solution pond) accounts for the upper limit of the individual total ratio in feasible solution pond (or infeasible solution).
11. a kind of schedule scheme evaluation and system of selection according to claim 10 based on hierarchical optimization, it is characterized in that: described step 4. in according to main optimization aim and suboptimization target pass judgment on, hierarchical optimization, separate with the feasible solution pond in branch feasible solution pond does not have the two kinds of situations of separating.
12. a kind of schedule scheme evaluation and system of selection based on hierarchical optimization according to claim 11, it is characterized in that: separate when the feasible solution pond, its process may further comprise the steps:
1. for separating in the feasible solution pond, press the fitness height, select the less a collection of individuality of diversity factor of fitness value, individual number satisfies the qualification of proportion threshold value;
2. based on this batch individuality, select an individuality that satisfies the suboptimization target most as optimum schedule scheme.
13. a kind of schedule scheme evaluation and system of selection based on hierarchical optimization according to claim 11, it is characterized in that: do not have when the feasible solution pond and separate, its process may further comprise the steps:
1. for separating in the infeasible solution pond, press the fitness height, select the less a collection of individuality of diversity factor of fitness value, individual number satisfies the qualification of proportion threshold value;
2. based on this batch individuality, select an individuality that satisfies main optimization aim most as optimum schedule scheme.
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| CN101859100A (en) * | 2010-06-18 | 2010-10-13 | 杭州电子科技大学 | Improved particle swarm optimization method based on streamline production scheduling of fuzzy due date |
| CN104570997A (en) * | 2014-10-22 | 2015-04-29 | 华中科技大学 | Method for discharge and processing production scheduling integration optimization of metal structure components |
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| CN101859100A (en) * | 2010-06-18 | 2010-10-13 | 杭州电子科技大学 | Improved particle swarm optimization method based on streamline production scheduling of fuzzy due date |
| CN104570997A (en) * | 2014-10-22 | 2015-04-29 | 华中科技大学 | Method for discharge and processing production scheduling integration optimization of metal structure components |
| CN104570997B (en) * | 2014-10-22 | 2017-08-11 | 华中科技大学 | One kind is used for hardware blanking and processing scheduling integrated optimization method |
| TWI571810B (en) * | 2014-12-01 | 2017-02-21 | 財團法人資訊工業策進會 | Production performance management device and production performance management method thereof |
| CN107315395A (en) * | 2016-12-23 | 2017-11-03 | 台晶(宁波)电子有限公司 | One kind production automatic error-correcting program system and method |
| CN110648037A (en) * | 2018-06-27 | 2020-01-03 | 深圳联友科技有限公司 | Finished automobile production evaluation method and device |
| CN110794788A (en) * | 2019-11-18 | 2020-02-14 | 国机工业互联网研究院(河南)有限公司 | Production scheduling device, method, equipment and computer readable storage medium |
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