An Experimental Study of Hybridizing Cultural Algorithms and Local Search

Research output: Contribution to journalArticle


Colleges, School and Institutes


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 languageEnglish
Pages (from-to)1-17
Number of pages17
JournalInternational Journal of Neural Systems
Issue number1
Publication statusPublished - 1 Feb 2008


  • meta-heuristic, Iterated Local Search, Cultural Algorithms, global optimization, continuous optimization