Search space reduction technique for constrained optimization with tiny feasible space

Abu S.S.M. Barkat Ullah, Ruhul Sarker, David Cornforth

Research output: A Conference proceeding or a Chapter in BookConference contribution

17 Citations (Scopus)

Abstract

The hurdles in solving Constrained Optimization Problems (COP) arise from the challenge of searching a huge variable space in order to locate feasible points with acceptable solution quality. It becomes even more challenging when the feasible space is very tiny compare to the search space. Usually, the quality of the initial solutions influences the performance of the algorithm in solving such problems. In this paper, we discuss an Evolutionary Agent System (EAS) for solving COPs. In EAS, we treat each individual in the population as an agent. To enhance the performance of EAS for solving COPs with tiny feasible space, we propose a Search Space Reduction Technique (SSRT) as an initial step of our algorithm. SSRT directs the selected infeasible agents in the initial population to move towards the feasible space. The performance of the proposed algorithm is tested on a number of test problems and a real world case problem. The experimental results show that SSRT not only improves the solution quality but also speed up the processing time of the algorithm.

Original languageEnglish
Title of host publicationGECCO'08
Subtitle of host publicationProceedings of the 10th Annual Conference on Genetic and Evolutionary Computation 2008
EditorsConor Ryan
Place of PublicationUnited States
PublisherAssociation for Computing Machinery (ACM)
Pages881-888
Number of pages8
ISBN (Print)9781605581309
DOIs
Publication statusPublished - 15 Dec 2008
Externally publishedYes
Event10th Annual Genetic and Evolutionary Computation Conference, GECCO 2008 - Atlanta, GA, United States
Duration: 12 Jul 200816 Jul 2008

Publication series

NameGECCO'08: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation 2008

Conference

Conference10th Annual Genetic and Evolutionary Computation Conference, GECCO 2008
CountryUnited States
CityAtlanta, GA
Period12/07/0816/07/08

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