Single-piece workshop scheduling method based on immune genetic algorithm

An immune genetic algorithm and workshop scheduling technology, applied in the fields of genetic law, calculation, genetic model, etc., can solve problems such as premature convergence, difficulty in achieving optimization effect, etc., to improve fitness value, improve solution effect, and speed up convergence speed Effect

Pending Publication Date: 2020-04-03
SHANGHAI UNIV
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  • Abstract
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AI Technical Summary

Problems solved by technology

When the genetic algorithm is used to solve the single-piece workshop scheduling problem, it is prone to premature convergence, which makes the algorithm fall into a local optimum during the optimization process, and it is difficult to achieve a better optimization effect. Therefore, it is necessary to carry out research and improve the genetic algorithm.

Method used

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  • Single-piece workshop scheduling method based on immune genetic algorithm
  • Single-piece workshop scheduling method based on immune genetic algorithm
  • Single-piece workshop scheduling method based on immune genetic algorithm

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Embodiment Construction

[0056] The present invention will be further described below in conjunction with drawings and embodiments.

[0057] Such as figure 1 As shown, a single-piece workshop scheduling method based on immune genetic algorithm, the operation steps are as follows: Step 1: Determine the operating parameters, Step 2: Generate the initial population, Step 3: Calculate individual fitness, Step 4: Update the memory cell bank, Step 5: Individual concentration evaluation, Step 6: Individual promotion and inhibition, Step 7: Crossover operation, Step 8: Mutation operation, Step 9: Vaccine extraction, Step 10: Vaccination, Step 11: Immune selection, Step 12: Elite retention Strategy, Step 13: Terminate Discrimination.

[0058] The specific instructions for the above steps are as follows:

[0059] Step 1. Determine the operating parameters:

[0060] The operating parameters of the immune genetic algorithm: the population size is generally 20-100, the crossover probability is generally 0.4-0.9...

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Abstract

The invention discloses a single-piece workshop scheduling method based on an immune genetic algorithm. The method comprises the following operation steps of: 1, determining operation parameters, 2, generating an initial population; 3, performing individual fitness calculation; 4, updating a memory cell bank; 5, evaluating an individual concentration; 6, performing individual promotion and inhibition; 7, performing crossover operation; 8, performing mutation operation;9, extracting a vaccine; 10, performing vaccination; 11, performing immunoselection; 12, adopting an elitism strategy; and 13,terminating discriminating. When the method provided by the invention is adopted to solve single-piece workshop scheduling, a satisfactory scheduling scheme can be more effectively solved, and the production efficiency is improved.

Description

technical field [0001] The invention relates to a single-piece workshop scheduling method based on immune genetic algorithm. Operations such as extraction and inoculation of high-quality individual processing sequence vaccines are added to the genetic algorithm, and the mixed immune genetic algorithm is used to solve the single-piece workshop scheduling problem. Background technique [0002] Job scheduling is an important link in arranging production job planning. Its main task is to determine the processing sequence of workpieces after knowing the product types, quantities and production hours on the order, and allocate corresponding production equipment for production and processing. For the same batch of workpieces to be processed, different production schedules will result in different completion times. Therefore, the purpose of job scheduling is to shorten the production cycle through reasonable workpiece processing sequence scheduling. [0003] When solving the job sh...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06N3/12
CPCG06Q10/04G06Q10/0633G06N3/126
Inventor 黄宗南陆云鹏曹炼干嘉伟
Owner SHANGHAI UNIV
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