Research on Improved NSGA-Ⅱ for Flexible Job Shop Scheduling Problems in Textile Workshop
In the textile production scheduling field,the traditional manual scheduling approach has been difficult to meet the current urgent requirements for the efficient use of machines and improve production efficiency.This paper develops a multi-objective mathematical model of the flexible job shop scheduling problem(FJSP)with the optimization objectives of maximum completion time and minimum total machine load.And an improved NSGA-Ⅱ algorithm(INSGA-Ⅱ)is proposed to solve the problem.The main innovations of this paper are as follows:First,a two-layer operation-and machine-based coding approach is used in INSGA-Ⅱ.Second,a hybrid population initialization strategy is adopted to improve the initial quality of the population.Third,a variable neighborhood search strategy based on the number of iterations is designed to improve the local search capability while reducing the invalid search.Finally,the proposed algorithm is compared with other algorithms(MOEA/D,MOEA/DD,and NSGA-Ⅱ)on the test sets MK01-MK09 and abz05-abz09.The effectiveness of the INSGA-Ⅱ in solving the FJSP is demonstrated by experimental results.
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