Optimal Scheduling and Decision Making Method for Dynamic Flexible Job Shop

doi:10.16182/j.issn1004731x.joss.20-0732

Abstract

Abstract: For multi-objective dynamic flexible job-shop scheduling, an improved multi-objective differential evolution algorithm is proposed. The adaptive cross-mutation operator is introduced into the differential evolution algorithm to improve its global search capability. The fast non-dominated sorting method based on immunological principles is introduced to improve the quality of the solution set in the selection and sorting. An improved TOPSIS-G1-EVM comprehensive decision-making method is proposed. The comprehensive weight of G1-EVM is calculated by Nash equilibrium theory. The comprehensive weight and TOPSIS evaluation system are combined to evaluate each dispatching scheme. The experimental results show that the optimal scheduling algorithm is superior in the optimization ability and the effectiveness of the comprehensive decision-making method.

Key words: flexible workshop, dynamic scheduling, multi objective differential evolution algorithm, TOPSIS-G1-EVM, comprehensive decision making

CLC Number:

TP391.9

Wang Yan, Ding Yu. Optimal Scheduling and Decision Making Method for Dynamic Flexible Job Shop[J]. Journal of System Simulation, 2020, 32(11): 2073-2083.

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