具有装车效率与负载均衡约束的分布式柔性流水车间调度问题研究

Research on Distributed Flexible Flow Shop Scheduling Problem with Loading Efficiency and Load Balancing Constraints

中文关键词:  生产调度  分布式柔性流水车间  约束优化问题  NSGA-II

Key Words:production scheduling  distributed flexible flow shop  constrained optimization problem  NSGA-II

中文摘要:

      本研究以总成本和最大完工时间为优化目标，基于非支配排序遗传算法（NSGA-II）的框架，使用多交叉操作融合策略和约束处理技术进行算法改进，构建了兼具装车效率与负载均衡约束的分布式柔性流水车间调度模型。根据配置典型分布式柔性流水车间的某生活用纸制造企业的真实数据，生成多组算例进行仿真实验，验证改进算法的有效性和优越性。结果表明，与NSGA-II相比，改进NSGA-II求解得到的生产调度方案平均总成本降低了约1.91%，平均最大完工时间缩短了约4.47%。

Abstract:

      With total cost and makespan as optimization objectives， based on the Non-dominated Sorting Genetic Algorithm （NSGA-II） framework， the algorithm was improved by using multi-crossover operation fusion strategy and constraint handling techniques， and a distributed flexible flow shop scheduling model that combines loading efficiency and load balancing constraints was constructed in this study. According to the actual data sourced from a household paper manufacturing enterprise which configured a typical distributed flexible flow shop， several examples of simulation experiments were generated to verify the effectiveness and superiority of the improved algorithm. The results showed that compared with NSGA-II， the production scheduling scheme obtained from improved NSGA-II had an average total cost reduction of about 1.91% and an average makespan reduction of about 4.47%.