Considering the transportation constraints in the scheduling of flexible job-shop for aerospace composite materials,a scheduling model was established with the goal of minimizing the completion time to solve this model,an improved two-popula-tion hybrid genetic algorithm was proposed.Based on the characteristics of the problem,a three-layer real number encoding and the corresponding decoding scheme were designed for the three sub-problems of operation sequencing,machine selection,and transportation constraints.A mixed initialization was adopted to improve the population quality,and a crossover operator was employed for global search during the evolutionary process.A local search strategy based on machine load balancing and variable neighborhood was designed for the two-population,enhancing both global and local search capabilities.Compared with the con-trast algorithm,the BPRD index for 9 out of the 10 test examples is obtained optimally,the APRD index is obtained optimally for all examples,and the t-test shows a significant difference,verifying the superiority of the proposed algorithm.The algorithm was applied to an actual aerospace composite materials manufacturing system,realizing the scheduling of practical production activities and verifying its feasibility.
维普
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