关键词: 三阶段装配流水线, 调度, 分布估计算法, 优化, 概率分布模型, 信息熵

Abstract: Aiming at a certain kind of three-stage assembly flowshop scheduling problem which was Three-Stage Assembly Flowshop Scheduling Problem with Sequence-Dependent Setup Times (TSAFSP_SDST),an Adaptive Hybrid Estimation of Distribution Algorithm (AHEDA) was presented to minimize the weighted sum of average completion time and maximum tardiness.The generation mechanism of initial population and initial probability distribution model were proposed to make probability distribution model accumulate the high quality solutions'information properly,which could improve the search ability of AHEDA at the initial stage of evolution.To enhance AHEDA's global search ability,the adaptive update scheme based on information entropy was designed for probability distribution model,and the new population generation method was also constructed to keep excellent and good pattern.An Insert-based neighbor search was introduced to improve the local search ability.The effectiveness of the presented AHEDA was verified by computational experiments and comparisons.

Key words: three-stage assembly flowshop, scheduling, estimation of distribution algorithm, optimization, probability distribution model, information entropymation entropy