Flexible job shop scheduling method based on multistage neighborhood structure and hybrid genetic algorithm

A hybrid genetic algorithm and flexible operation technology, applied in the field of job shop scheduling

Pending Publication Date: 2021-03-30
BEIJING UNIV OF TECH +1
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Problems solved by technology

[0004] The invention is a new hybrid genetic algorithm for solving the problem of flexible workshop scheduling

Method used

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  • Flexible job shop scheduling method based on multistage neighborhood structure and hybrid genetic algorithm
  • Flexible job shop scheduling method based on multistage neighborhood structure and hybrid genetic algorithm
  • Flexible job shop scheduling method based on multistage neighborhood structure and hybrid genetic algorithm

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Embodiment Construction

[0058] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0059] The present invention is a flexible job shop scheduling method based on a new hybrid genetic algorithm, which combines a hybrid heuristic initialization method and multi-level neighborhood search based on key processes to solve the flexible job shop scheduling problem. The algorithm flow is as follows figure 1 shown. Now with figure 2 The example problem shown is illustrated.

[0060] Step 1: Enter the basic data of the problem, including the number of workpieces 4, the number of equipment 6, and the processing time of each process of each workpiece on optional equipment.

[0061] Step 2: Set the algorithm parameters: the population size is 50, the crossover probability is 0.8, the mutation probability is 0.1, and the number of iterations is 200.

[0062] Step 3: Generate an initialization population, namely: 50 initial individuals, and the e...

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Abstract

The invention discloses a flexible job shop scheduling method based on a multistage neighborhood structure and a hybrid genetic algorithm, and the method comprises an initialization strategy of a hybrid heuristic rule, and can effectively improve the quality and diversity of an initial solution. Variable neighborhood descent search is embedded in a universal genetic algorithm framework, a novel multi-level neighborhood structure based on a key process is effectively searched, and the exploration capability of a solution space is greatly improved. The defects of low solving precision, low convergence speed and easiness in falling into local optimum of a general genetic algorithm for a flexible job shop scheduling problem can be overcome, a higher-quality scheduling scheme is obtained, the production efficiency is further improved, and the cost is reduced.

Description

technical field [0001] The present invention relates to a job shop scheduling technology, especially a method for flexible job shop job scheduling based on genetic algorithm, specifically a new hybrid genetic algorithm that combines variable neighborhood descent search based on improved multi-level neighborhood structure Flexible workshop scheduling method. Background technique [0002] In the face of fierce market competition, manufacturing companies must continuously improve production efficiency, shorten product launch time, and reduce production costs. Although the introduction of advanced equipment and technology can improve manufacturing efficiency, it requires a lot of cost investment; optimizing the mature production process, the improvement effect is uncertain, and there are technical risks. On the basis of existing equipment and technology, through workshop planning and scheduling, the workpieces are arranged in a more reasonable order on the most suitable machine...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/04G06N3/00G06N3/12
CPCG06Q10/06316G06Q50/04G06N3/006G06N3/126Y02P90/30
Inventor 刘志峰汪俊龙张彩霞丁国智郭诗瑶
Owner BEIJING UNIV OF TECH
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