Conference paper
Multi-modal search with convex bounding neighbourhood
2006 International Conference on Machine Learning and Cybernetics, pp.2081-2086
2006 International Conference on Machine Learning and Cybernetics (Dalian, China, 13/08/2006–16/08/2006)
2006
Abstract
This paper presents a new dynamic method of subpopulation in solving multi-modal search problems with evolutionary algorithms. The new method identify the modes found at each generation and equalises the subpopulation sizes assigned to each mode. Modes are identified sequentially starting with the highest fitness mode. Mode membership is determined by successive grouping of fitness dominated convex bounding neighbours, starting from the fittest individual. This new dynamic modal subpopulation approach is able to find a representative sample of optima for multi-modal landscape with infinite number of global and local optima with uneven heights and non-uniform distribution. The algorithm also facilitates parallel implementation
Details
- Title
- Multi-modal search with convex bounding neighbourhood
- Authors/Creators
- D.H.M. Nguyen (Author/Creator) - Murdoch UniversityK.P. Wong (Author/Creator) - Hong Kong Polytechnic UniversityC. Chung (Author/Creator) - Hong Kong Polytechnic University
- Publication Details
- 2006 International Conference on Machine Learning and Cybernetics, pp.2081-2086
- Conference
- 2006 International Conference on Machine Learning and Cybernetics (Dalian, China, 13/08/2006–16/08/2006)
- Identifiers
- 991005542504807891
- Murdoch Affiliation
- School of Engineering Science
- Language
- English
- Resource Type
- Conference paper
- Note
- Appears In: Proceedings of the 2006 International Conference on Machine Learning and Cybernetics
Metrics
190 File views/ downloads
90 Record Views