Modelling and optimisation of energy consumption and profit-oriented multi-parallel partial disassembly line balancing problem

Based on the actual requirements of recycling enterprises, this study proposes a multi-parallel partial disassembly line balancing problem (MPPDLBP). Four objectives, the number of shared workstations, workstation load balancing index, energy consumption, and profit, need to be optimised in MPPDLBP....

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Bibliographic Details
Published in:International journal of production economics Vol. 262; p. 108928
Main Authors: Liang, Wei, Zhang, Zeqiang, Yin, Tao, Zhang, Yu, Wu, Tengfei
Format: Journal Article
Language:English
Published: Elsevier B.V 01.08.2023
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ISSN:0925-5273, 1873-7579
Online Access:Get full text
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Summary:Based on the actual requirements of recycling enterprises, this study proposes a multi-parallel partial disassembly line balancing problem (MPPDLBP). Four objectives, the number of shared workstations, workstation load balancing index, energy consumption, and profit, need to be optimised in MPPDLBP. To address the MPPDLBP, this study further constructs a mixed-integer nonlinear programming (MINLP) model and designs a suitable mechanism of encoding and decoding. Meanwhile, partial disassembly is adopted in this study because recycling enterprises aim for low energy consumption and high profits. In addition, the positions of the best values for each objective are defined as the best disassembly levels. Furthermore, this study proposes a genetic and tabu search algorithm (GATS) for optimising the MPPDLBP effectively. The superior performance of the proposed GATS is verified by comparing it with other effective algorithms in existing literature. Finally, this study optimises a hybrid instance and provides decision-makers with multiple low-energy and high-profit disassembly schemes. •A multi-parallel partial disassembly line balancing problem was investigated.•A mixed-integer non-linear programming model was established.•An encoding and decoding method based on the proposed problem was constructed.•A genetic and tabu search algorithm was developed.•Variation trend of energy consumption and profit with disposal depth was analyzed.
ISSN:0925-5273
1873-7579
DOI:10.1016/j.ijpe.2023.108928