关键词: 多目标, 置换流水车间调度, 遗传算法, 变邻域搜索

Abstract: An improved genetic algorithm is proposed for multi-objective of Permutation Flowshop Scheduling Problem （PFSP） to optimize the makespan and total flow time. In order to keep the diversity of the population, the initial population is generated by combining heuristic algorithm and random algorithm in the proposed algorithm. The procedure of evolution is completed with selection, crossover, mutation operation and update strategy. When population evolutionary stagnated, the re-initialization mechanism is introduced to restore diversity. In addition, a variable neighborhood search algorithm is designed to accelerate population convergence and jump out of local optimum. Compared with several other optimization algorithms through experiment on the benchmarks, the results show that the proposed algorithm in both solution quality and stability is superior to other algorithms.

Key words: multi-objective, permutation flowshop scheduling, genetic algorithm, variable neighborhood search