TY - JOUR
T1 - Dual-Objective Program and Scatter Search for the Optimization of Disassembly Sequences Subject to Multiresource Constraints
AU - Guo, Xiwang
AU - Liu, Shixin
AU - Zhou, Mengchu
AU - Tian, Guangdong
N1 - Funding Information:
Manuscript received January 18, 2017; revised June 2, 2017 and July 12, 2017; accepted July 21, 2017. Date of publication August 22, 2017; date of current version July 2, 2018. This paper was recommended for publication by Associate Editor R. Uzsoy and Editor S. Reveliotis upon evaluation of the reviewers’ comments. This work was supported in part by NSFC under Grant 61573089 and Grant 51405075, and in part by the Funds for International Cooperation and Exchange of the National Natural Science Foundation of China under Grant 51561125002. (Xiwang Guo and Shixin Liu contributed equally to this work.) (Corresponding author: MengChu Zhou; Guangdong Tian.) X. Guo is with the Computer and Communication Engineering College, Liaoning Shihua University, Fushun 113001, China, and also with the Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ 07102 USA (e-mail: x.w.guo@163.com).
Publisher Copyright:
© 2004-2012 IEEE.
PY - 2018/7
Y1 - 2018/7
N2 - The effective dismantling of discarded products regardless being used or not is critically important to their reuse, recovery, and recycling. However, the existing product disassembly planning methods pay little or no attention to resource constraints, e.g., limited numbers of disassembly operators and tools. Thus, a resulting plan when being executed may be ineffective in practice. This paper presents a dual-objective optimization model for selective disassembly sequences by considering multiresource constraints such that disassembly profit is maximized and time is minimized. A scatter search is adopted to solve the proposed dual-objective optimization model. It embodies the generation of diverse initial solutions, global assessment of objective functions, a crossover combination operator, a local search strategy for improved solutions, and a reference set update method. To analyze the effect of different weights on its performance, simulations are conducted on different products. Its effectiveness is verified by comparing its optimization results and those of genetic local search. Note to Practitioners - This work deals with a sequence modeling and planning problem of product disassembly. It establishes a novel dual-objective optimization model for product disassembly subject to multiresource constraints. Previously, such a problem is handled through a methodology based on the optimization of a single objective, i.e., disassembly time or cost. The resultant solution is insufficient without fully considering disassembly resources, e.g., labors and tools. Also, in an actual disassembly process, a decision-maker may want to maximize disassembly profit, as well as minimize disassembly time. This work considers both objectives and proposes scatter search to solve disassembly problems. The results demonstrate that the proposed approach can solve them effectively. The obtained solutions give decision makers some desired choices to select a right disassembly process when an actual product is disassembled.
AB - The effective dismantling of discarded products regardless being used or not is critically important to their reuse, recovery, and recycling. However, the existing product disassembly planning methods pay little or no attention to resource constraints, e.g., limited numbers of disassembly operators and tools. Thus, a resulting plan when being executed may be ineffective in practice. This paper presents a dual-objective optimization model for selective disassembly sequences by considering multiresource constraints such that disassembly profit is maximized and time is minimized. A scatter search is adopted to solve the proposed dual-objective optimization model. It embodies the generation of diverse initial solutions, global assessment of objective functions, a crossover combination operator, a local search strategy for improved solutions, and a reference set update method. To analyze the effect of different weights on its performance, simulations are conducted on different products. Its effectiveness is verified by comparing its optimization results and those of genetic local search. Note to Practitioners - This work deals with a sequence modeling and planning problem of product disassembly. It establishes a novel dual-objective optimization model for product disassembly subject to multiresource constraints. Previously, such a problem is handled through a methodology based on the optimization of a single objective, i.e., disassembly time or cost. The resultant solution is insufficient without fully considering disassembly resources, e.g., labors and tools. Also, in an actual disassembly process, a decision-maker may want to maximize disassembly profit, as well as minimize disassembly time. This work considers both objectives and proposes scatter search to solve disassembly problems. The results demonstrate that the proposed approach can solve them effectively. The obtained solutions give decision makers some desired choices to select a right disassembly process when an actual product is disassembled.
KW - Disassembly
KW - genetic local search (GLS)
KW - modeling and simulation
KW - scatter search (SS)
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U2 - 10.1109/TASE.2017.2731981
DO - 10.1109/TASE.2017.2731981
M3 - Article
AN - SCOPUS:85028504174
SN - 1545-5955
VL - 15
SP - 1091
EP - 1103
JO - IEEE Transactions on Automation Science and Engineering
JF - IEEE Transactions on Automation Science and Engineering
IS - 3
ER -