Flexible job shop scheduling method based on multi-species coevolution

A workshop scheduling and flexible operation technology, applied in data processing applications, instruments, calculations, etc., can solve problems such as complex solution space, insufficient algorithm performance, and difficulty in finding high-quality scheduling solutions, and achieve simple solution space , the effect of maintaining diversity

Inactive Publication Date: 2010-12-01
HUAZHONG UNIV OF SCI & TECH
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Problems solved by technology

The genetic algorithm has a strong global search ability, but there are still the following problems in solving the flexible job shop scheduling problem: the flexible job shop scheduling problem contains two sub-problems (machine selection sub-problem and process sequencing

Method used

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  • Flexible job shop scheduling method based on multi-species coevolution
  • Flexible job shop scheduling method based on multi-species coevolution
  • Flexible job shop scheduling method based on multi-species coevolution

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Embodiment Construction

[0032] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0033] refer to figure 1 and figure 2 , a flexible job shop scheduling method based on multi-population co-evolution, including the following steps:

[0034] Step 1, parameter setting:

[0035] Assuming that the number of workpieces is N, this method contains N+1 sub-populations, of which N machines select the sub-problem population, and 1 process sorting sub-problem population size. Set the threshold maxGen of the number of algorithm loop iterations, and the population size P of the machine selection sub-problem 1 , the tournament selection factor k 1 , the crossover probability is P c1 , the mutation probability is Pm1 , the tournament selection factor k 2 , the population size of the process ordering subproblem is P 2 , crossover probability P c2 , the mutation probability P m2 .

[0036] Step 2, initialize the population:

[003...

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Abstract

The invention provides a flexible job shop scheduling method based on multi-species coevolution, which belongs to the field of shop scheduling, and mainly overcomes the disadvantage that a flexible job shop scheduling method based on a genetic algorithm can not be exerted fully. The method comprises the main steps of: 1. setting parameters; 2. initializing species according to a set coding method; 3. calculating the fitness value of each chromosome in each species according to a set method, and recording the optimum fitness value and the constitute chromosomes thereof; 4. carrying out multi-species coevolution: carrying out evolution operations, i.e. chiasmata and variation, to chromosomes in each subspecies, and evaluating new chromosomes; and 5. judging whether a method termination criteria is achieved or not: if so, terminating the method and outputting the optimum fitness value and the constitute chromosomes thereof; and otherwise, jumping to the step 4. The invention can be used to obtain a high-quality scheduling scheme suitable for practical production of shops, can shorten production time, and can be used for scheduling management and optimization of the production process of shops.

Description

technical field [0001] The invention belongs to the field of workshop scheduling, and in particular relates to a flexible job workshop scheduling method, which is used for scheduling management and optimization of the workshop production process. Background technique [0002] Workshop production scheduling is the basis of manufacturing system, and the optimization of production scheduling is the core of advanced manufacturing technology and modern management technology. Relevant data show that 95% of the time in the manufacturing process is consumed in non-cutting processes. Therefore, scientifically formulating a production scheduling plan can shorten the product production cycle, control the work-in-progress inventory in the workshop, improve the rate of product delivery and improve enterprise productivity. It plays a vital role and has important theoretical value and practical significance for the modernization of advanced manufacturing enterprises. [0003] In the tradi...

Claims

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Application Information

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IPC IPC(8): G06Q10/00G06Q10/06
Inventor 李新宇高亮邵新宇张利平王晓娟
Owner HUAZHONG UNIV OF SCI & TECH
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