A New Chaotic-Based Approach for Multi-Objective Optimization
Multi-objective optimization problems (MOPs) have been widely studied during the last decades. In this paper, we present a new approach based on Chaotic search to solve MOPs. Various Tchebychev scalarization strategies have been investigated. Moreover, a comparison with state of the art algorithms o...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-08-01
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| Series: | Algorithms |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-4893/13/9/204 |
| Summary: | Multi-objective optimization problems (MOPs) have been widely studied during the last decades. In this paper, we present a new approach based on Chaotic search to solve MOPs. Various Tchebychev scalarization strategies have been investigated. Moreover, a comparison with state of the art algorithms on different well known bound constrained benchmarks shows the efficiency and the effectiveness of the proposed Chaotic search approach. |
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| ISSN: | 1999-4893 |