A Multi-objective Flexible Job Shop Scheduling Method Based on Two-layer Genetic Algorithm

Abstract

A multi-objective flexible job shop scheduling method based on a two-layer genetic algorithm, which is characterized by improving the traditional genetic algorithm so that the population optimized by the genetic algorithm within a limited time has a high quality; at the same time, changing the traditional genetic algorithm For the solution mode of multi-objective problems, a two-layer solution framework is proposed, which has significantly improved the solution quality compared with the traditional genetic algorithm. The invention optimizes the crossover strategy and mutation strategy and deletes the selection operator. The present invention combines the above-mentioned improved genetic algorithm with fast non-dominated sorting and congestion degree calculation modules, and designs a special process framework for it, which is called double-layer genetic algorithm. The algorithm can obtain an excellent non-dominated solution set in a limited time, has good practicability, and can be well applied to the actual workshop scheduling.

Description

technical field [0001] 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 [0002] 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 scheduling problem: each...

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Problems solved by technology

[0005] 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 two-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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