A combined MA-GA approach for solving constrained optimization problems

Abu Saleh Shah Muhammad Barkat Ullah, Ruhul Sarker, David Cornforth

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

5 Citations (Scopus)

Abstract

Many real world decision processes require to solve optimization problems. In this paper, an integrated Multiagent-Genetic Algorithm (MA-GA) is considered to solve constrained optimization problems. The applied approach is new in the literature for solving constrained optimization problems. Ten benchmark problems are used to test the performance of the approach and the results show impressive performance.

Original languageEnglish
Title of host publicationProceedings - 6th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2007; 1st IEEE/ACIS International Workshop on e-Activity, IWEA 2007
EditorsRoger Lee, Morshed U. Chowdhury, Sid Ray, Thuy Lee
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages382-387
Number of pages6
ISBN (Print)0769528414, 9780769528410
DOIs
Publication statusPublished - 1 Dec 2007
Externally publishedYes
Event6th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2007; 1st IEEE/ACIS International Workshop on e-Activity, IWEA 2007 - Melbourne, VIC, Australia
Duration: 11 Jul 200713 Jul 2007

Publication series

NameProceedings - 6th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2007; 1st IEEE/ACIS International Workshop on e-Activity, IWEA 2007

Conference

Conference6th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2007; 1st IEEE/ACIS International Workshop on e-Activity, IWEA 2007
CountryAustralia
CityMelbourne, VIC
Period11/07/0713/07/07

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