Function optimization in nonstationary environment using steady state genetic algorithms with aging of individuals

Author

Ghosh, Ashish ; Tsutsui, Shigeyoshi ; Tanak, Hideo

Author_Institution

Machine Intelligence Unit, Indian Stat. Inst., Calcutta, India

fYear

1998

fDate

4-9 May 1998

Firstpage

666

Lastpage

671

Abstract

The authors explore the utility of the concept of aging of individuals in the context of steady state GAs for nonstationary function optimization. Age of an individual is used as an additional factor in addition to the objective functional value in order to determine its effective fitness value. Age of a newly generated individual is taken as zero, and in every iteration it is increased by one. Individuals undergoing genetic operations are selected based on the effective fitness value, which changes dynamically. This helps to maintain diversity in the population and is useful to trace changes in environment. Simulation results show some promise for the utility of the present technique for nonstationary function optimization

Keywords

genetic algorithms; simulation; effective fitness value; genetic operations; individual aging; iteration; newly generated individual age; nonstationary environment; nonstationary function optimization; objective functional value; population diversity; simulation; steady state genetic algorithms; Aging; Engineering management; Environmental management; Genetic algorithms; Industrial engineering; Information management; Information science; Machine intelligence; Steady-state; Tellurium;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on

Conference_Location

Anchorage, AK

Print_ISBN

0-7803-4869-9

Type

conf

DOI

10.1109/ICEC.1998.700119

Filename

700119