基于双种群遗传算法的废旧智能手机拆卸序列规划

doi:10.3901/JME.2021.17.226

机械工程学报 ›› 2021, Vol. 57 ›› Issue (17): 226-235.doi: 10.3901/JME.2021.17.226

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基于双种群遗传算法的废旧智能手机拆卸序列规划

尹凤福, 杜泽瑞, 李林, 梁振宁, 安瑞, 王瑞东, 刘广阔

青岛科技大学机电工程学院青岛 266061

收稿日期:2020-08-16 修回日期:2021-03-09 发布日期:2021-11-16
通讯作者: 李林(通信作者),男,1987年出生,博士。主要研究机电产品的绿色设计与制造。E-mail:ll@qust.edu.cn
作者简介:尹凤福,男,1969年出生,博士,教授,博士研究生导师。主要研究机电产品的绿色设计与制造。E-mail:yinff@qust.edu.cn;杜泽瑞,男,1994年出生,硕士研究生。主要研究机电产品的拆解技术。E-mail:1073081050@qq.com
基金资助:
国家科技重点研发计划资助项目（2018YFC1902300）。

Disassembly Sequence Planning of Used Smartphone Based on Dual-population Genetic Algorithm

YIN Fengfu, DU Zerui, LI Lin, LIANG Zhenning, AN Rui, WANG Ruidong, LIU Guangkuo

College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao 266000

Received:2020-08-16 Revised:2021-03-09 Published:2021-11-16

摘要/Abstract

摘要： 为解决手机大批量报废带来的环境和资源问题，对废旧智能手机进行了拆卸回收技术的研究。针对废旧智能手机的完全拆卸，提出了一种基于双种群遗传算法（Genetic algorithm，GA）的拆卸序列规划方法，通过分析智能手机的结构零部件信息，特别是零部件间的约束关系，建立了五元组混合图拆卸模型，并利用连接矩阵和优先矩阵，描述了拆卸智能手机的约束关系。以拆卸时间和回收利润作为决策目标，同步考虑了影响拆卸时间和回收利润的多个指标，创新构建了拆卸双目标决策优化数学模型，并设计了一种双种群GA搜索优化解，确定智能手机最优或次优的拆卸序列方案。以“iPhone6”智能手机为实例，利用所设计的算法求解了其对应的优化拆卸序列，并与经验拆卸和基本GA对比，结果显示拆卸时间缩短了11.2%和5.6%，回收利润提高了6.6%和3.0%，验证了该方法的可行性和高效性。

关键词: 废旧智能手机, 双目标优化, 双种群GA, 拆卸序列规划

Abstract: In order to solve the environmental and resource problems caused by the mass scrapping of mobile phones, the dismantling and recycling technology of waste smartphones is studied. For the complete disassembly of waste smartphones, a disassembly sequence planning (DSP) based on dual population GA (genetic algorithm) is proposed. By analyzing the structural component information of smartphones, especially the constraints between the parts, a five-tuple mixed graph disassembly model is established, and the connection matrix and priority matrix are used to describe the constraint relationship of disassembly of smartphones. Taking disassembly time and recovery profit as the decision goals, considering multiple indicators that affect the disassembly time and recovery profit simultaneously, a mathematical model of disassembly dual-objective decision optimization is constructed innovatively. A dual-population GA search optimization solution is designed to determine the optimal or suboptimal disassembly sequence scheme. Taking the "iPhone6" smartphone as an example, the corresponding optimized disassembly sequence is solved using the designed algorithm. Compared with the experience disassembly and basic GA, the results show that the disassembly time is shortened by 11.2% and 5.6%, and the recovery profit increased by 6.6% and 3.0%, which proves the applicability and efficiency of the method.

Key words: waste smartphones, dual-objective optimization, dual-population GA, disassembly sequence planning

中图分类号:

TP18
X76

尹凤福, 杜泽瑞, 李林, 梁振宁, 安瑞, 王瑞东, 刘广阔. 基于双种群遗传算法的废旧智能手机拆卸序列规划[J]. 机械工程学报, 2021, 57(17): 226-235.

YIN Fengfu, DU Zerui, LI Lin, LIANG Zhenning, AN Rui, WANG Ruidong, LIU Guangkuo. Disassembly Sequence Planning of Used Smartphone Based on Dual-population Genetic Algorithm[J]. Journal of Mechanical Engineering, 2021, 57(17): 226-235.

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基于双种群遗传算法的废旧智能手机拆卸序列规划

Disassembly Sequence Planning of Used Smartphone Based on Dual-population Genetic Algorithm

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