DocumentCode
3282437
Title
Differential Evolution with Graph-Based Speciation by Competitive Hebbian Rules
Author
Takahama, Tetsuyuki ; Sakai, Shin´ichi
Author_Institution
Dept. of Intell. Syst., Hiroshima City Univ., Hiroshima, Japan
fYear
2012
fDate
25-28 Aug. 2012
Firstpage
445
Lastpage
448
Abstract
Differential evolution (DE) is an evolutionary algorithm and has been successfully applied to optimization problems including non-linear, non-differentiable, non-convex and multimodal functions. However, it is still difficult to solve hard problems such as multimodal problems and problems with ridge structures. in this study, we propose a new speciation method "graph-based speciation" to keep the diversity of the search points and realize the global search. Also, we utilize the species-best strategy that can realize the global search using speciation and the local search around the seeds of species. It is expected that the efficiency and the robustness of DE can be improved by using the strategy. the advantage of the proposed method is shown by solving some benchmark problems including multimodal problems and problems with ridge structures.
Keywords
Hebbian learning; concave programming; evolutionary computation; graph theory; nonlinear functions; search problems; competitive Hebbian rules; differential evolution; evolutionary algorithm; global search; graph-based speciation; local search; multimodal functions; multimodal problems; nonconvex functions; nondifferentiable functions; nonlinear functions; optimization problems; ridge structures; search points; species-best strategy; Evolutionary computation; Optimization; Robustness; Search problems; Sociology; Statistics; Vectors; Delaunay diagram; competitive Hebbian rules; differential evolution; speciation;
fLanguage
English
Publisher
ieee
Conference_Titel
Genetic and Evolutionary Computing (ICGEC), 2012 Sixth International Conference on
Conference_Location
Kitakushu
Print_ISBN
978-1-4673-2138-9
Type
conf
DOI
10.1109/ICGEC.2012.83
Filename
6457121
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