面向高效低碳的切削参数与柔性作业车间调度集成建模与优化  

Integrated optimization of cutting parameters and flexible job shop scheduling based on improved discrete gravity search algorithm

作　　者：詹欣隆 张超勇[1] 孟磊磊 连裕翔 薛燕社 ZHAN Xinlong;ZHANG Chaoyong;MENG Leilei;LIAN Yuxiang;XUE Yanshe(State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;School of Computer Science, Liaocheng University, Liaocheng 252059,China)

机构地区：[1]华中科技大学数字制造装备与技术国家重点实验室,湖北武汉430074 [2]聊城大学计算机学院,山东聊城252059

出　　处：《计算机集成制造系统》2021年第12期3519-3535,共17页Computer Integrated Manufacturing Systems

基　　金：国家自然科学基金面上资助项目(51875429);国家自然科学基金国际(地区)合作与交流资助项目(51861165202);山东省自然科学基金资助项目(ZR2021QE195)。

摘　　要：传统制造业切削参数优化与柔性作业车间调度优化通常独立进行,将切削参数与调度方案之间进行集成优化,能更好地解决车间高效低碳优化问题。以制造过程碳排放和最大完工时间为目标,建立切削参数与柔性作业车间调度高效低碳集成优化模型,提出一种改进的离散化引力搜索算法(IDGSA)求解机器切削参数与调度方案之间的协同优化问题。根据集成优化问题特性,首次设计了一种工件序列—机器序列—切削参数模式三层编码方式,并且不同的编码方式采用不同的初始化方法,保证初始解的质量以及多样性。针对集成优化问题的三层编码特性,提出一种新的竞选机制,竞选出最优双层序列,与精英质点的工件序列交叉产生新的质点,引导算法向真实Pareto前沿靠近;所提算法中采用多点交叉和变邻域搜索实现分散搜索与集中搜索有机平衡。通过对比改进的非支配排序遗传算法(NSGA-Ⅱ)和离散化引力搜索算法(DGSA),以及将提出切削参数可变的集成优化方法与3种切削参数不可变的优化方法进行对比,验证了所提改进算法的优越性和集成策略的有效性。To solve the low-carbon optimization problem,the cutting parameters with the flexible job shop scheduling problem was integrated to optimize.The multi-objective integrated optimization model of flexible job shop scheduling was established by considering actual constraints,and an Improved Discrete Gravity Search Algorithm(IDGSA)was proposed to solve the collaborative optimization problem between machine cutting parameters and scheduling scheme.For the characteristics of integrated optimization problems,a new three-layer coding of workpiece sequence-machine sequence-cutting parameter mode was proposed.Different initialization methods were used for different encoding methods to ensure the quality and diversity of the initial solution.According to the three-layer coding characteristics of the integrated optimization problem,a new election mechanism was proposed to select the optimal two-layer sequence,which intersected with the workpiece sequence of elite particles to generate new particles and guide the algorithm to approach the true frontier of Pareto.The multi-point crossover and variable neighborhood search were used to realize the balance of decentralized search with centralized search.The superiorities of the proposed improved algorithm and integration method WERE verified by comparison experiments.

关 键 词：切削参数 柔性作业车间调度 低碳制造 多目标优化 离散化引力搜索算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]