Multiverse Optimization Algorithm for Stochastic Biobjective Disassembly Sequence Planning Subject to Operation Failures
Disassembly is an essential step in a remanufacturing process via which valuable parts and material of end-of-life (EOL) products can be well reused and resource waste is reduced. Disassembly sequence planning focuses on finding the best disassembly sequence for a given EOL product by considering ec...
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| Vydáno v: | IEEE transactions on systems, man, and cybernetics. Systems Ročník 52; číslo 2; s. 1041 - 1051 |
|---|---|
| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
New York
IEEE
01.02.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Témata: | |
| ISSN: | 2168-2216, 2168-2232 |
| On-line přístup: | Získat plný text |
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| Abstract | Disassembly is an essential step in a remanufacturing process via which valuable parts and material of end-of-life (EOL) products can be well reused and resource waste is reduced. Disassembly sequence planning focuses on finding the best disassembly sequence for a given EOL product by considering economic and environmental performance. In a practical disassembly process, one may face a disassembly operation failure risk due to the difficulty of knowing EOL products' exact information in advance. Despite its importance in impacting disassembly outcomes, the existing work fails to consider it comprehensively. This work proposes a stochastic biobjective DSP problem with the objectives of maximizing disassembly profit and minimizing energy consumption by doing so. A chance-constrained programming model is established, where a chance constraint ensures a fixed confidence level of disassembly failure. To solve it efficiently, a multiobjective multiverse optimization algorithm with stochastic simulation is proposed. Experiments are carried out on four products. Results demonstrate that it outperforms some state-of-the-art algorithms in terms of solution performance. |
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| AbstractList | Disassembly is an essential step in a remanufacturing process via which valuable parts and material of end-of-life (EOL) products can be well reused and resource waste is reduced. Disassembly sequence planning focuses on finding the best disassembly sequence for a given EOL product by considering economic and environmental performance. In a practical disassembly process, one may face a disassembly operation failure risk due to the difficulty of knowing EOL products' exact information in advance. Despite its importance in impacting disassembly outcomes, the existing work fails to consider it comprehensively. This work proposes a stochastic biobjective DSP problem with the objectives of maximizing disassembly profit and minimizing energy consumption by doing so. A chance-constrained programming model is established, where a chance constraint ensures a fixed confidence level of disassembly failure. To solve it efficiently, a multiobjective multiverse optimization algorithm with stochastic simulation is proposed. Experiments are carried out on four products. Results demonstrate that it outperforms some state-of-the-art algorithms in terms of solution performance. |
| Author | Zhou, MengChu Fu, Yaping Sedraoui, Khaled Guo, Xiwang Qi, Liang |
| Author_xml | – sequence: 1 givenname: Yaping surname: Fu fullname: Fu, Yaping email: fuyaping0432@163.com organization: School of Business, Qingdao University, Qingdao, China – sequence: 2 givenname: MengChu orcidid: 0000-0002-5408-8752 surname: Zhou fullname: Zhou, MengChu email: zhou@njit.edu organization: Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA – sequence: 3 givenname: Xiwang orcidid: 0000-0002-9142-1251 surname: Guo fullname: Guo, Xiwang email: x.w.guo@163.com organization: Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA – sequence: 4 givenname: Liang orcidid: 0000-0002-0762-5607 surname: Qi fullname: Qi, Liang email: qiliangsdkd@163.com organization: College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China – sequence: 5 givenname: Khaled surname: Sedraoui fullname: Sedraoui, Khaled email: sedraoui@yahoo.com organization: Department of Electrical and Computer Engineering, Faculty of Engineering, and Center of Research Excellence in Renewable Energy and Power Systems, King Abdulaziz University, Jeddah, Saudi Arabia |
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| SubjectTerms | Algorithms Confidence intervals Constraint modelling Disassembly failure risk disassembly sequence planning (DSP) problem Disassembly sequences Dismantling End of life Energy consumption Hidden Markov models multiobjective multiverse optimization algorithm Multiple objective analysis Optimization Optimization algorithms Planning Remanufacturing Stochastic processes stochastic simulation Task analysis Uncertainty |
| Title | Multiverse Optimization Algorithm for Stochastic Biobjective Disassembly Sequence Planning Subject to Operation Failures |
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