Multi-Objective Discrete Brainstorming Optimizer to Solve the Stochastic Multiple-Product Robotic Disassembly Line Balancing Problem Subject to Disassembly Failures
Robots are now widely used in product disassembly lines, which significantly improves end-of-life (EOL) product disassembly efficiency. Most of the current research on disassembly line balancing problems focuses on decomposing one product. More than one product can be disassembled concurrently, whic...
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MDPI AG
2023-03-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/11/6/1557 |
| _version_ | 1797610306764013568 |
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| author | Gongdan Xu Zhiwei Zhang Zhiwu Li Xiwang Guo Liang Qi Xianzhao Liu |
| author_facet | Gongdan Xu Zhiwei Zhang Zhiwu Li Xiwang Guo Liang Qi Xianzhao Liu |
| author_sort | Gongdan Xu |
| collection | DOAJ |
| description | Robots are now widely used in product disassembly lines, which significantly improves end-of-life (EOL) product disassembly efficiency. Most of the current research on disassembly line balancing problems focuses on decomposing one product. More than one product can be disassembled concurrently, which can further improve the efficiency. Moreover, uncertainty such as the depreciation of EOL products, may result in disassembly failure. In this research, a stochastic multi-product robotic disassembly line balancing model is established using an AND/OR graph. It takes the precedence relationship, cycle constraint, and disassembly failure into consideration to maximize the profit and minimize the energy consumption for disassembling multiple products. A Pareto-improved multi-objective brainstorming optimization algorithm combined with stochastic simulation is proposed to solve the problem. Furthermore, by conducting experiments on some real cases and comparing with four state-of-the-art multi-objective optimization algorithms, i.e., the multi-objective discrete gray wolf optimizer, artificial bee colony algorithm, nondominated sorting genetic algorithm II, and multi-objective evolutionary algorithm based on decomposition, this paper validates its excellent performance in solving the concerned problem. |
| first_indexed | 2024-03-11T06:13:39Z |
| format | Article |
| id | doaj.art-bc4ba2969f14453aa7954c7af6020f36 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-11T06:13:39Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-bc4ba2969f14453aa7954c7af6020f362023-11-17T12:30:18ZengMDPI AGMathematics2227-73902023-03-01116155710.3390/math11061557Multi-Objective Discrete Brainstorming Optimizer to Solve the Stochastic Multiple-Product Robotic Disassembly Line Balancing Problem Subject to Disassembly FailuresGongdan Xu0Zhiwei Zhang1Zhiwu Li2Xiwang Guo3Liang Qi4Xianzhao Liu5Institute of Systems Engineering, Macau University of Science and Technology, Taipa, Macau 999078, ChinaCollege of Computer and Communication Engineering, Liaoning Petrochemical University, Fushun 113001, ChinaInstitute of Systems Engineering, Macau University of Science and Technology, Taipa, Macau 999078, ChinaCollege of Computer and Communication Engineering, Liaoning Petrochemical University, Fushun 113001, ChinaComputer Science and Technology, Shandong University of Science and Technology, Qingdao 266590, ChinaHitachi Building Technology (Guangzhou) Co., Ltd., Guangzhou 510670, ChinaRobots are now widely used in product disassembly lines, which significantly improves end-of-life (EOL) product disassembly efficiency. Most of the current research on disassembly line balancing problems focuses on decomposing one product. More than one product can be disassembled concurrently, which can further improve the efficiency. Moreover, uncertainty such as the depreciation of EOL products, may result in disassembly failure. In this research, a stochastic multi-product robotic disassembly line balancing model is established using an AND/OR graph. It takes the precedence relationship, cycle constraint, and disassembly failure into consideration to maximize the profit and minimize the energy consumption for disassembling multiple products. A Pareto-improved multi-objective brainstorming optimization algorithm combined with stochastic simulation is proposed to solve the problem. Furthermore, by conducting experiments on some real cases and comparing with four state-of-the-art multi-objective optimization algorithms, i.e., the multi-objective discrete gray wolf optimizer, artificial bee colony algorithm, nondominated sorting genetic algorithm II, and multi-objective evolutionary algorithm based on decomposition, this paper validates its excellent performance in solving the concerned problem.https://www.mdpi.com/2227-7390/11/6/1557disassembly failuremachine learningmultiple product disassemblyrobotic disassembly line balancing problem |
| spellingShingle | Gongdan Xu Zhiwei Zhang Zhiwu Li Xiwang Guo Liang Qi Xianzhao Liu Multi-Objective Discrete Brainstorming Optimizer to Solve the Stochastic Multiple-Product Robotic Disassembly Line Balancing Problem Subject to Disassembly Failures Mathematics disassembly failure machine learning multiple product disassembly robotic disassembly line balancing problem |
| title | Multi-Objective Discrete Brainstorming Optimizer to Solve the Stochastic Multiple-Product Robotic Disassembly Line Balancing Problem Subject to Disassembly Failures |
| title_full | Multi-Objective Discrete Brainstorming Optimizer to Solve the Stochastic Multiple-Product Robotic Disassembly Line Balancing Problem Subject to Disassembly Failures |
| title_fullStr | Multi-Objective Discrete Brainstorming Optimizer to Solve the Stochastic Multiple-Product Robotic Disassembly Line Balancing Problem Subject to Disassembly Failures |
| title_full_unstemmed | Multi-Objective Discrete Brainstorming Optimizer to Solve the Stochastic Multiple-Product Robotic Disassembly Line Balancing Problem Subject to Disassembly Failures |
| title_short | Multi-Objective Discrete Brainstorming Optimizer to Solve the Stochastic Multiple-Product Robotic Disassembly Line Balancing Problem Subject to Disassembly Failures |
| title_sort | multi objective discrete brainstorming optimizer to solve the stochastic multiple product robotic disassembly line balancing problem subject to disassembly failures |
| topic | disassembly failure machine learning multiple product disassembly robotic disassembly line balancing problem |
| url | https://www.mdpi.com/2227-7390/11/6/1557 |
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