MOEA/D-SQA: a multi-objective memetic algorithm based on decomposition
A multi-objective memetic algorithm based on decomposition is proposed in this article, in which a simplified quadratic approximation (SQA) is employed as a local search operator for enhancing the performance of a multi-objective evolutionary algorithm based on decomposition (MOEA/D). The SQA is use...
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| Published in: | Engineering optimization Vol. 44; no. 9; pp. 1095 - 1115 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Abingdon
Taylor & Francis
01.09.2012
Taylor & Francis Ltd |
| Subjects: | |
| ISSN: | 0305-215X, 1029-0273 |
| Online Access: | Get full text |
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| Summary: | A multi-objective memetic algorithm based on decomposition is proposed in this article, in which a simplified quadratic approximation (SQA) is employed as a local search operator for enhancing the performance of a multi-objective evolutionary algorithm based on decomposition (MOEA/D). The SQA is used for a fast local search and the MOEA/D is used as the global optimizer. The multi-objective memetic algorithm based on decomposition, i.e. a hybrid of the MOEA/D with the SQA (MOEA/D-SQA), is designed to balance local versus global search strategies so as to obtain a set of diverse non-dominated solutions as quickly as possible. The emphasis of this article is placed on demonstrating how this local search scheme can improve the performance of MOEA/D for multi-objective optimization. MOEA/D-SQA has been tested on a wide set of benchmark problems with complicated Pareto set shapes. Experimental results indicate that the proposed approach performs better than MOEA/D. In addition, the results obtained are very competitive when comparing MOEA/D-SQA with other state-of-the-art techniques. |
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| Bibliography: | SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 0305-215X 1029-0273 |
| DOI: | 10.1080/0305215X.2011.632008 |