This paper is a contribution towards the identification of the best optimization algorithm to detect convenient disassembly sequences for end-of-life industrial products. Three methodologies are proposed for comparison: Artificial Colony Optimization, Genetic Algorithms and Simulated Annealing. These algorithms are compared using case studies including partial and full disassembly.
A comparative experimental study of heuristics for multi objective disassembly planning / Marchionna, P.; Paradiso, S.; Percoco, Gianluca. - In: INTERNATIONAL JOURNAL OF MECHANICAL & MECHANICS ENGINEERING. - ISSN 2227-2771. - 16:5(2016), pp. 54-62.
A comparative experimental study of heuristics for multi objective disassembly planning
PERCOCO, Gianluca
2016-01-01
Abstract
This paper is a contribution towards the identification of the best optimization algorithm to detect convenient disassembly sequences for end-of-life industrial products. Three methodologies are proposed for comparison: Artificial Colony Optimization, Genetic Algorithms and Simulated Annealing. These algorithms are compared using case studies including partial and full disassembly.File in questo prodotto:
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