Modelling and solving profit-oriented U-shaped partial disassembly line balancing problem

•Profit-oriented U-shaped partial disassembly line balancing problem is studied.•Mixed-integer linear programming model is developed for the proposed problem.•The proposed model solves the small-size problems optimally.•The cuckoo search algorithm is developed and improved for the considered problem...

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Bibliographic Details
Published in:Expert systems with applications Vol. 183; p. 115431
Main Authors: Li, Zixiang, Janardhanan, Mukund Nilakantan
Format: Journal Article
Language:English
Published: New York Elsevier Ltd 30.11.2021
Elsevier BV
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ISSN:0957-4174, 1873-6793
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Summary:•Profit-oriented U-shaped partial disassembly line balancing problem is studied.•Mixed-integer linear programming model is developed for the proposed problem.•The proposed model solves the small-size problems optimally.•The cuckoo search algorithm is developed and improved for the considered problem.•Experimental tests demonstrate the superiority of the proposed algorithm. Disassembly lines are utilized frequently to disassemble the end-of-life products completely or partially to retain the valuable components for remanufacturing or recycling. This research introduces and solves the profit-oriented U-shaped partial disassembly line balancing problem (PUPDLBP) for the first time. A 0–1 integer linear programming model is formulated to tackle the PUPDLBP with AND/OR precedence, which is capable of solving the small-size instances optimally. As the considered problem is NP-hard, a novel discrete cuckoo search (DCS) algorithm is implemented and improved to solve the considered problem. The proposed DCS employs a two-phase decoding procedure to handle the precedence constraint, and new population update and new method to select and replace the abandoned individuals to achieve the proper balance between exploitation and exploration. Case studies demonstrate that the U-shaped line might obtain the larger total profit than a straight line. The comparative study shows that the improvements enhance the performance of DCS by a significant margin. The proposed algorithm outperforms CPLEX solver when solving large-sized instances and produce competing performance in comparison with 11 other algorithms.
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ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2021.115431