Facing the characteristics of aerospace component inspection with many varieties,small batches,central-ized inspection tasks,large differences in test procedures and difficulty in data reuse,a scheduling framework for multi-category dual-feature detection resources was established.A multi-objective optimization model with the mini-mum average time consumption and the minimum total cost as the optimization goals was constructed,and an im-proved Multi-Objective Optimization Evolutionary algorithm based on Decomposition(MOEA/D)algorithm based on local optimization was proposed.The algorithm considered multi-stage real number encoding and decoding rules,and combined with local optimization operators and adaptive penalty functions based on the feasibility of the solution to ensure the quality and diversity of individuals in the population.The improved MOEA/D algorithm was used in actual cases and compared with other algorithms,and the effectiveness and superiority in solving such problems were verified.
关键词
元器件检测/调度优化/多目标优化/基于分解的多目标进化算法
Key words
component inspection/scheduling optimization/multi-objective optimization/multi-objective optimization evolutionary algorithm based on decomposition
维普
万方数据