考虑不确定拆卸时间的异步并行拆卸序列规划  

Research on asynchronous parallel disassembly sequence planning considering uncertain disassembly time

作　　者：邱栋 彭奕童 陈兆芳 QIU Dong;PENG Yitong;CHEN Zhaofang(School of Management,Fujian University of Technology,Fuzhou 350118,China)

机构地区：[1]福建理工大学管理学院,福建福州350118

出　　处：《福建理工大学学报》2025年第1期57-63,共7页JOURNAL OF FUJILAN UNIVERSITY OF TECHNOLOGY

基　　金：福建省社会科学规划重点项目(FJ2024MGCA027);福州市社会科学规划重点项目(2023FZB05)。

摘　　要：因拆卸时间受操作者技能熟练程度、产品自身结构以及组成材料变化等多方面影响而存在不确定性的问题,基于灰数提出不确定拆卸时间的异步并行拆卸序列规划方法。在考虑拆卸最大规定时间约束、工作站先后顺序以及并行拆卸序列执行长度等约束条件的基础上建立最大拆卸收益与最小拆卸时间为目标的数学模型,提出一种改进人工蜂群算法。用矩阵编码构造可行解并使用锦标赛选择替代轮盘赌,在侦查蜂阶段设计一种基于潜能值的更新策略,提出一种新型的协同对比方法获得非劣解。通过算法对比验证改进算法的可行性,最后由笔记本电脑的拆卸实例来验证优化模型的有效性,实验结果表明:异步并行拆卸的经济效益提升了23.1%,拆卸时间缩短了12.7%。Due to the uncertainty of disassembly time caused by various factors such as the proficiency of the operator’s skills,the structure of the product itself,and changes in the composition materials,an asynchronous parallel disassembly sequence planning problem with uncertain disassembly time is proposed based on grey numbers.On the basis of considering constraints such as the maximum specified dismantling time,workstation sequence,and parallel dismantling sequence execution length,a mathematical model is established with the objectives of maximum dismantling benefits and minimum dismantling time,and an improved artificial bee colony algorithm is proposed.The feasible solution is constructed by matrix encoding and tournament selection is used to replace the roulette wheel.An update strategy based on potential value is designed in the scout bee phase.A new collaborative comparison method is proposed to obtain non-inferior solutions.The feasibility of the improved algorithm was verified through algorithm comparison,and the effectiveness of the optimization model was finally validated through a disassembly example of a laptop.Experimental results show that the economic benefits of asynchronous parallel disassembly increased by 23.1%,and the disassembly time was shortened by 12.7%.

关 键 词：异步并行拆卸序列规划 灰数 不确定性 改进人工蜂群算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构] TH165[自动化与计算机技术—计算机科学与技术]