改进GSO算法的成套订单调度和维修联合优化  

Joint Optimization of Whole-set Order Scheduling and Equipment Maintenance Based on Improved GSO Algorithm

作　　者：杨晓梅 张宇琼[2] 李文汇 官开 YANG Xiao-mei;ZHANG Yu-qiong;LI Wen-hui;GUAN Kai(Key Research Bases for Humanities and Social Sciences in Shanxi:Research Center for Innovation and Development of Equipment Manufacturing Industry,Taiyuan University of Science and Technology,Taiyuan 030024,China;School of Economics and Management,Taiyuan University of Science and Technology,Taiyuan 030024,China)

机构地区：[1]山西省人文社科重点基地:装备制造业创新发展研究中心,太原030024 [2]太原科技大学经济与管理学院,太原030024

出　　处：《太原科技大学学报》2023年第5期469-475,共7页Journal of Taiyuan University of Science and Technology

基　　金：国家自然科学基金(71701140);山西省自然科学基金(201801D121170,201801D121166);太原科技大学博士启动资金项目(20202027)。

摘　　要：基于对生产调度和设备维修间相关关系的分析,设计了成套订单调度和设备维修的联合策略。该策略根据故障率的大小来判定对应的设备维修活动或后续的调度任务,根据该策略,以加工作业顺序和预防性维修阈值为决策变量,加权成套订单数最大为优化目标构建了联合决策模型。利用对调度问题特点和设备故障机理的分析,设计了一个改进的萤火虫算法,将其运用于求解所提出的联合决策模型,并通过数值实验和灵敏度分析,验证了改进算法的可行性和模型的有效性。Through analyzing the relevance of production scheduling and equipment maintenance,a joint strategy of whole-set order scheduling and equipment maintenance is designed.In this strategy,the corresponding maintenance activities and subsequent scheduling tasks are determined by the failure rate.According to this strategy,a joint decision-making model is obtained.The decision variables of this model include the order of processing operations,preventive maintenance thresholds as decision variables,and maximizing the number of weighted whole-set orders is the optimization goal.Aided by the analysis of the characteristics of the scheduling problem and the mechanism of equipment failure,an improved Glowworm Swarm Optimization algorithm is designed and applied to solve the proposed joint decision-making model.Numerical experiments and sensitivity analysis verify the feasibility of the improved algorithm and the effectiveness of the model.

关 键 词：成套订单调度 预防性维修 萤火虫优化算法(GSO) 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]