Abstract: To solve the problem of long production cycle and high energy consumption in the production of cold-drawn seamless steel pipes and to realize the intelligent and green scheduling,the re-entrant hybrid flow shop scheduling problem with continuous batch processing machines (RHFSP-CBPM) was studied.A mathematical model was formulated with considering the buffer of the batch processing machines.Then,an Improved Multi-Objective Evolutionary Algorithm based on Decomposition (IMOEA/D) was developed to solve the problem,and an operation-based encoding method and a balanced decoding method were proposed.A local search strategy and diversity enhancement strategy were designed according to the diversity metrics,and the diversity of Pareto solutions was improved by local searching.The numerical experiments were carried out and the results showed that the proposed model and the developed algorithm could solve the proposed problem effectively.

Key words: hybrid flow shop scheduling, re-entrant, continuous batch processing machine, buffer, improved multi-objective evolutionary algorithm based on decomposition

摘要： 为了解决冷拔无缝钢管生产周期长、能源消耗高的问题,实现生产调度的智能化、绿色化,研究了带连续式批处理机的可重入混合流水车间调度问题。首先考虑批处理机缓冲区的影响,构建了调度优化模型;然后设计了改进的基于分解的多目标进化算法用于该问题,提出了基于工序的编码方案和均衡考虑完工时间与能耗的解码方案,根据多样性指标的高低设计了局部搜索和多样性增强策略,并通过对最优解局部搜索来提高解的多样性;最后,通过对不同算例的实验,验证了所提算法可以高效地求解带连续式批处理机的可重入混合流水车间调度问题。

关键词: 混合流水车间调度, 可重入, 连续式批处理机, 缓冲区, 改进的基于分解的多目标进化算法