Title :
Multi-Modal Search with Convex Bounding Neighbourhood
Author :
Nguyen, D.H.M. ; Wong, K.P. ; Chung, C.Y.
Author_Institution :
Sch. of Eng. Sci., Murdoch Univ., WA
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
Keywords :
convex programming; dynamic programming; evolutionary computation; search problems; statistical distributions; dynamic modal subpopulation method; evolutionary algorithm; fitness dominated convex bounding neighbourhood; mode membership; multimodal landscape; multimodal search problem solving; Bioinformatics; Computational intelligence; Cybernetics; Electronic mail; Evolution (biology); Evolutionary computation; Genomics; Laboratories; Machine learning; Parallel algorithms; Partitioning algorithms; Search problems; Stochastic processes; Tagging; Multi-modal search; evolutionary computation; parallel algorithm; subpopulation techniques;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.258347
