An efficient metaheuristics for a sequence-dependent disassembly planning

JOURNAL OF CLEANER PRODUCTION

卷:245

Article

Ren, Yaping¹  Meng, Leilei²  Zhang, Chaoyong³  Zhao, Fu^4,5  Saif, Ulah⁶  Huang, Aihua⁵  Mendis, Gamini P.⁵  Sutherland, John W.⁵ 

[1] Jinan Univ Zhuhai Campus, Sch Intelligent Syst Sci & Engn, Zhuhai 519070, Peoples R China

[2] Liaocheng Univ, Sch Comp Sci, Liaocheng 252059, Shandong, Peoples R China

[3] Huazhong Univ Sci & Technol, Key Lab Digital Mfg Equipment & Technol, Wuhan 430074, Hubei, Peoples R China

[4] Purdue Univ, Sch Mech Engn, W Lafayette, IN 47907 USA

[5] Purdue Univ, Environm & Ecol Engn, W Lafayette, IN 47907 USA

[6] Univ Engn & Technol, Dept Ind Engn, Taxila, Pakistan

关键词: Remanufacturing;    Disassembly planning;    Sequence-dependent;    AND/OR graph;    Metaheuristics;   

DOI  :  10.1016/j.jclepro.2019.118644

来源: Elsevier

【 摘 要 】

Disassembly planning (DP) is critical in remanufacturing and value recovery from end-of-life products and has attracted increasing attention due to the recent resurgence of research on circular economy. DP problem is NP-hard and its complexity increases exponentially with the size of problem. Sequence-dependent cost due to varying quality of the parts to be retrieved further increases the complexity of DP problems. This paper investigates the DP considering sequence-dependent costs among disassembly operations. A mathematical model is proposed with the objective to maximize the recovery profit using an AND/OR graph (AOG) subject to sequence-dependent costs. A novel two-phase heuristic method is developed to effectively generate feasible disassembly sequence according to the AOG in reasonable computation time. In addition, an improved genetic algorithm (IGA) is proposed to solve the problem, in combination with the presented two-phase heuristic. The performance of IGA is measured on a series of test problem instances against exact methods including CPLEX and an iterative method. Results indicate that IGA successfully find the near-optimal/optimal solutions and outperforms the other methods in terms of computation time. Finally, the proposed method is applied to compute the disassembly solution of a HG5-20 triaxial five speed mechanical transmission. Compared to the existing disassembly solutions of the transmission, the obtained solutions by IGA can shorten about 11% disassembly time and increase by approximately 7% recovery profit. (C) 2019 Elsevier Ltd. All rights reserved.

【 授权许可】

Free