Abstract
In this paper the performance of the Cultural Algorithms-Iterated Local Search (CA-ILS), a new continuous optimization algorithm, is empirically studied on multimodal test functions proposed in the Special Session on Real-Parameter Optimization of the 2005 Congress on Evolutionary Computation. It is compared with state-of-the-art methods attending the Session to find out whether the algorithm is effective in solving difficult problems. The test results show that CA-ILS may be a competitive method, at least in the tested problems. The results also reveal the classes of problems where CA-ILS can work well and/or not well.
Original language | English |
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Pages (from-to) | 1-17 |
Number of pages | 17 |
Journal | International Journal of Neural Systems |
Volume | 18 |
Issue number | 1 |
DOIs | |
Publication status | Published - 1 Feb 2008 |
Keywords
- meta-heuristic
- Iterated Local Search
- Cultural Algorithms
- global optimization
- continuous optimization