Multi-target flexible job shop scheduling method based on double-layer genetic algorithm

Abstract

A multi-target flexible job shop scheduling method based on a double-layer genetic algorithm is characterized in that a traditional genetic algorithm is improved, so that a population optimized by thegenetic algorithm within limited time has high quality; meanwhile, the solving mode of the traditional genetic algorithm for the multi-target problem is changed, a double-layer solving framework is provided, and compared with the traditional genetic algorithm, the solving quality is obviously improved. According to the method, the crossover strategy and the mutation strategy are optimized, and the selection operator is deleted. The improved genetic algorithm is combined with a rapid non-dominated sorting and congestion degree calculation module, a special process framework is designed for theimproved genetic algorithm, and the improved genetic algorithm is called as a double-layer genetic algorithm. According to the algorithm, an excellent non-dominated solution set can be obtained within limited time, and the algorithm has good practicability and can be well applied to actual workshop scheduling.

Description

[0001] technology neighborhood [0002] The invention relates to a production scheduling technology, especially a flexible workshop height technology, specifically a multi-objective flexible job workshop scheduling method based on a two-layer genetic algorithm. Background technique [0003] In the current fierce market competition, customers have explosively diversified and personalized demands on products. The production mode of enterprise products will gradually change from enterprise-oriented to user-oriented. In the face of this change, the traditional manual scheduling method can no longer meet the requirements of enterprises, and information and intelligent means must be used to deal with this problem. Workshop scheduling technology is one of the key factors to realize high efficiency, high flexibility and high reliability of manufacturing enterprises. Generally, when studying the job shop scheduling problem, the research will be based on the classic job shop schedulin...

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Problems solved by technology

[0006] The purpose of the present invention is that when the single genetic algorithm used in the existing workshop scheduling is applied to multi-objective search, the obtained non-dominated solution sets are often concentrated in a specific range, and it is impossible to obtain an excellent solution in the overall situation. , it often falls into the dilemma of local optimum after many iterations. At this time, because the population diversity is not good enough, it is impossible to continue searching. A multi-objective flexible job shop scheduling method based on double-layer genetic algorithm is invented. Based on fast non-dominated sorting and congestion calculation, it optimizes the quality of the population through a two-layer design, improves the efficiency of the algorithm, and realizes the rapid scheduling of the workshop

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