Analysis of Some Mating and Collaboration Strategies in Evolutionary Algorithms

Author

Gog, Anca ; Chira, Camelia ; Dumitrescu, D. ; Zaharie, Daniela

Author_Institution

Dept. of Comput. Sci., Babes Bolyai Univ., Cluj-Napoca, Romania

fYear

2008

fDate

26-29 Sept. 2008

Firstpage

538

Lastpage

542

Abstract

The selection of mates in an evolutionary algorithm can significantly influence the exploration and the exploitation abilities of the search process. Currently there are several strategies to guide the mate selection or to restrict the mating pool. The aim of this paper is to analyze the behavior of a fitness guided mate selection strategy and of a collaboration strategy between population elements which use different mating rules. The behavior is analyzed empirically for mate selection in differential evolution algorithms by considering that the population is divided in two subpopulations characterized by different mating rules. The dynamics of these subpopulations sizes is also theoretically analyzed.

Keywords

evolutionary computation; search problems; behavior analysis; collaboration strategy; differential evolution algorithm; evolutionary algorithm; fitness guided mate selection strategy; population element; search process; Algorithm design and analysis; Computer science; Context modeling; Design optimization; Evolutionary computation; International collaboration; Multiagent systems; Scientific computing; Terminology; Topology; differential evolution; evolutionary algorithms; exploration and exploitation; mating rules; subpopulation;

fLanguage

English

Publisher

ieee

Conference_Titel

Symbolic and Numeric Algorithms for Scientific Computing, 2008. SYNASC '08. 10th International Symposium on

Conference_Location

Timisoara

Print_ISBN

978-0-7695-3523-4

Type

conf

DOI

10.1109/SYNASC.2008.87

Filename

5204867