基于改进双档案多目标进化算法的柔性作业车间批量流混排调度  

Flexible Job-Shop lot-streaming intermingling scheduling based onimproved two-archive multi-objective evolutionary algorithm

作　　者：黄洋鹏 李玲玲 李丽[1] Huang Yangpeng;Li Lingling;Li Li(College of Engineering&Technology,Southwest University,Chongqing 400715,China)

机构地区：[1]西南大学工程技术学院,重庆400715

出　　处：《计算机应用研究》2024年第6期1669-1678,共10页Application Research of Computers

基　　金：国家自然科学基金资助项目(51905449);重庆市杰出青年科学基金资助项目(CSTB2022NSCQ-JQX0030);中央高校基本科研业务费专项资金资助项目(SWU-KT22023)。

摘　　要：针对柔性作业车间批量流调度问题,基于快速换模技术,考虑可变子批划分柔性、子批混排加工柔性、自动换模柔性和物料运输柔性,建立以最小化完工时间和加工子批总数为目标的混排调度优化模型,并提出一种改进双档案多目标进化算法以优化目标函数。基于进化算法框架,设计了基于超体积指标和基于改进帕累托支配的双档案筛选机制,以平衡种群的收敛性和多样性;针对批量流混排调度问题特征,在解码阶段提出正/逆解码和子批拆分左移策略,在邻域探索和全局搜索阶段分别设计子批划分和混排调度的自适应进化算子,以提高算法的全局搜索与局部搜索能力。基于不同规模算例,测试了提出算法与经典多目标算法的性能。实验结果表明,该算法在收敛性与多样性上具有明显优势。Aiming at the flexible Job-Shop lot-streaming scheduling problem,based on the single minute exchange of die(SMED),this paper established an intermingling scheduling optimization model with objections of minimizing the makespan and the total number of sub-lots,considering the flexibility of sublots splitting and sublots intermingling,automatic changeover and material transportation.Then it proposed an improved two-archive based multi-objective evolutionary algorithm to optimize the objective function.This algorithm adopted the framework of evolutionary algorithm.Based on the framework of evolutionary algorithm,it designed a two-archive based on hypervolume indicator and improved Pareto dominance to balance the convergence and diversity of the population.And according to the characteristics of lot-streaming intermingling problems,it proposed the forward/backward decoding and sublot splitting left-shift strategies in the decoding stage.In the stages of neighborhood exploration and global search,it designed adaptive evolution operators for lot splitting and sub-lot intermingling schemes respectively to improve the global search and local search capabilities of the algorithm.Based on different scale examples,it tested the performance of the proposed algorithm and the classical multi-objective algorithms.The experimental results show that the algorithm has obvious advantages in convergence and diversity.

关 键 词：作业车间 批量流调度 快速换模 多目标进化算法 解码策略 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置] TH165[自动化与计算机技术—控制科学与工程]