Abstract
Multi-objective optimization using an evolutionary computation technique is used extensively for solving conflicting multi-objective optimization problems. In this work, an improved strategy of multi-objective differential evolution (MODE) where the mutation strategy is changed to a trigonometric mutation approach is proposed. The proposed strategy along with other well known strategies of MODE is used to compare the performance metrics (such as convergence and divergence) with other evolutionary algorithms from the literature. The Pareto optimal solutions are obtained for benchmark test functions and are compared using several strategies of MODE. Improved strategies of MODE show a competitive performance when compared with other evolutionary multi-objective optimization algorithms (EMOAs).
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 4th Indian International Conference on Artificial Intelligence, IICAI 2009 |
| Pages | 933-948 |
| Number of pages | 16 |
| Publication status | Published - 2009 |
| Event | 4th Indian International Conference on Artificial Intelligence, IICAI 2009 - Tumkur, India Duration: Dec 16 2009 → Dec 18 2009 |
Other
| Other | 4th Indian International Conference on Artificial Intelligence, IICAI 2009 |
|---|---|
| Country | India |
| City | Tumkur |
| Period | 12/16/09 → 12/18/09 |
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Keywords
- Differential evolution
- Evolutionary algorithms
- Multi-objective optimization
- Optimization
- Trigonometric mutation
ASJC Scopus subject areas
- Artificial Intelligence