关键词: 大规模置换流水车间调度, 初始退火温度优化, 协同并行搜索, 开普勒型衰减函数

Abstract: To solve the large-scale permutation flowshop scheduling problem,an improved simulated annealing algorithm was proposed.The initial annealing temperature was optimized and the corresponding calculation function was given in the first step.Then,new solutions were generated by using the probability-based multi-strategy collaborative search,parallel search and memory function were introduced to improve the quality of solutions at the same time.Furthermore,to improve the convergence rate of solutions for large-scale problems,the “Kepler” attenuation function was selected as the temperature attenuation function.Under the goal of minimizing the maximum completion time,the large-scale problem (number of jobs >100) of Taillard benchmark,VRF benchmark and actual manufacturing workshop of engine connecting rod parts was taken as numerical values and engineering cases to verify the performance of the proposed algorithm.

Key words: permutation flowshop scheduling problem, initial annealing temperature optimization, cooperative parallel search, Kepler-type decay function