Multiresource-Constrained Selective Disassembly With Maximal Profit and Minimal Energy Consumption
Industrial products' reuse, recovery, and recycling are very important due to the exhaustion of ecological resources. Effective product disassembly planning methods can improve the recovery efficiency and reduce harmful impact on the environment. However, the existing approaches pay little atte...
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| Published in | IEEE transactions on automation science and engineering Vol. 18; no. 2; pp. 804 - 816 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
IEEE
01.04.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Industrial products' reuse, recovery, and recycling are very important due to the exhaustion of ecological resources. Effective product disassembly planning methods can improve the recovery efficiency and reduce harmful impact on the environment. However, the existing approaches pay little attention to disassembly resources, such as tools and operators that can significantly influence the optimal disassembly sequences. This article considers a multiobjective resource-constrained disassembly optimization problem modeled with timed Petri nets such that energy consumption is minimized, while disassembly profit is maximized. Since its solution complexity has exponential growth with the number of components in a product, a multiobjective genetic algorithm based on an external archive is used to solve it. Its effectiveness is verified by comparing it with nondominated sorting genetic algorithm II and a collaborative resource allocation strategy for a multiobjective evolutionary algorithm based on decomposition. Note to Practitioners -This article establishes a novel dual-objective optimization model for product disassembly subject to multiresource constraints. In an actual disassembly process, a decision-maker may want to minimize energy consumption and maximize disassembly profit. This article considers both objectives and proposes a multiobjective genetic algorithm based on an external archive to solve optimal disassembly problems. The experimental results show that the proposed approach can solve them effectively. The obtained solutions give decision-makers multiple choices to select the right disassembly process when an actual product is disassembled. |
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| AbstractList | Industrial products' reuse, recovery, and recycling are very important due to the exhaustion of ecological resources. Effective product disassembly planning methods can improve the recovery efficiency and reduce harmful impact on the environment. However, the existing approaches pay little attention to disassembly resources, such as tools and operators that can significantly influence the optimal disassembly sequences. This article considers a multiobjective resource-constrained disassembly optimization problem modeled with timed Petri nets such that energy consumption is minimized, while disassembly profit is maximized. Since its solution complexity has exponential growth with the number of components in a product, a multiobjective genetic algorithm based on an external archive is used to solve it. Its effectiveness is verified by comparing it with nondominated sorting genetic algorithm II and a collaborative resource allocation strategy for a multiobjective evolutionary algorithm based on decomposition. Note to Practitioners -This article establishes a novel dual-objective optimization model for product disassembly subject to multiresource constraints. In an actual disassembly process, a decision-maker may want to minimize energy consumption and maximize disassembly profit. This article considers both objectives and proposes a multiobjective genetic algorithm based on an external archive to solve optimal disassembly problems. The experimental results show that the proposed approach can solve them effectively. The obtained solutions give decision-makers multiple choices to select the right disassembly process when an actual product is disassembled. |
| Author | Zhou, MengChu Guo, Xiwang Liu, Shixin Qi, Liang |
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| SubjectTerms | Archives & records Biological system modeling Constraints Decision making Disassembly sequence Disassembly sequences Dismantling Ecological effects Energy consumption Evolutionary algorithms Genetic algorithms intelligent algorithm multiobjective Multiple objective analysis multiresource constraints Optimization Petri nets Petri nets (PNs) Planning Recovering Recycling Resource allocation Selective disassembly Sorting algorithms |
| Title | Multiresource-Constrained Selective Disassembly With Maximal Profit and Minimal Energy Consumption |
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