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EnglishAlgebraic evolutionary algorithms are an emerging class of meta-heuristics for combinatorial optimization based on strong mathematical foundations. In this paper we introduce a decomposition-based algebraic evolutionary algorithm, namely MOEA/DEP, in order to deal with multiobjective permutation-based optimization problems. As a case of study, MOEA/DEP has been experimentally validated on a multiobjective permutation flowshop scheduling problem (MoPFSP). In particular, the makespan and total flowtime objectives have been investigated. Experiments have been held on a widely used benchmark suite, and the obtained results have been compared with respect to the state-of-the-art Pareto fronts for MoPFSP. The experimental results have been analyzed by means of two commonly used performance metrics for multiobjective optimization. The analysis clearly shows that MOEA/DEP reaches new state-of-the-art results for the considered benchmark.
| Titolo: | MOEA/DEP: An Algebraic Decomposition-Based Evolutionary Algorithm for the Multiobjective Permutation Flowshop Scheduling Problem | |
| Autori: | SANTUCCI, Valentino (Corresponding) | |
| Data di pubblicazione: | 2018 | |
| Serie: | ||
| Handle: | http://hdl.handle.net/20.500.12071/12795 | |
| ISBN: | 978-3-319-77448-0 978-3-319-77449-7 | |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| paper26.pdf | Documento in Pre-print |  | Open Access Visualizza/Apri | |
| evocop2018.pdf | Versione Editoriale (PDF) | | Administrator Richiedi una copia |
http://hdl.handle.net/20.500.12071/12795
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