@article{d4e555cee520445f9b2b84288a0a3db2,
title = "An efficient metaheuristics for a sequence-dependent disassembly planning",
abstract = "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.",
author = "Yaping Ren and Leilei Meng and Chaoyong Zhang and Fu Zhao and Ulah Saif and Aihua Huang and Mendis, {Gamini P.} and Sutherland, {John W.}",
note = "Funding Information: This research is supported by the Funds for the Key Research and Development Program of Guangdong Province (Grant No. 2019B090921001 ), Guangzhou Leading Innovation Team Project (Grant No. 201909010006 ), National Natural Science Foundation of China (Grant No. 51575211 , 51875251 ), and the U.S. National Science Foundation (Grant No. 1512217 ). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Natural Science Foundation of China and the U.S. National Science Foundation. We are grateful to the editor and anonymous referees for their constructive comments to improve this paper. Appendix Fig. A1 The AND/OR graph of the radio set (product 4) in scenario 2. Fig. A1 Fig. A2 The AND/OR graph of the product in scenario 3. Fig. A2 Fig. A3 The AND/OR graph of the product in scenario 4. Fig. A3 Fig. A4 f performance comparison with different P c and P m for three products. Fig. A4 Fig. 5A The average f values of IGA for products 1, 2, 3 and 4 with different MaxIter and PopSize . Fig. 5A Fig. 6A The HG5-20 triaxial five speed mechanical transmission and its main parts. Fig. 6A Fig. 7A The AND/OR graph of the HG5-20 triaxial five speed mechanical transmission. Symbol {\textquoteleft}-{\textquoteright} is used to simplify the composition of subassemblies in the AND/OR graph. For example, A-L denotes the alphabetical order from A to L, i.e., A, B, C, D, E, F, G, H, I, J, K, and L. Fig. 7A Funding Information: This research is supported by the Funds for the Key Research and Development Program of Guangdong Province (Grant No. 2019B090921001), Guangzhou Leading Innovation Team Project (Grant No. 201909010006), National Natural Science Foundation of China (Grant No. 51575211, 51875251), and the U.S. National Science Foundation (Grant No. 1512217). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Natural Science Foundation of China and the U.S. National Science Foundation. We are grateful to the editor and anonymous referees for their constructive comments to improve this paper. Publisher Copyright: {\textcopyright} 2019 Elsevier Ltd",
year = "2020",
month = feb,
day = "1",
doi = "10.1016/j.jclepro.2019.118644",
language = "English (US)",
volume = "245",
journal = "Journal of Cleaner Production",
issn = "0959-6526",
publisher = "Elsevier Limited",
}