An agent-based memetic algorithm (AMA) for nonlinear optimization with equality constraints

Abu S.S.M. Barkat Ullah, Ruhul Sarker, Chris Lokan

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

8 Citations (Scopus)

Abstract

Over the last two decades several methods have been proposed for handling functional constraints while solving nonlinear optimization problems using Evolutionary Algorithms (EA). However EAs have inherent difficulty in dealing with equality constraints. This paper presents an Agent-based Memetic Algorithm (AMA) for solving nonlinear optimization problems with equality constraints. A new learning process for agents is introduced specifically for handling the equality constraints in the evolutionary process. The basic concept is to reach a point on the equality constraint from its current position by the selected individual agents. The proposed algorithm is tested on a set of standard benchmark problems. The preliminary results show that the proposed technique works very well on those benchmark problems.

Original languageEnglish
Title of host publication2009 IEEE Congress on Evolutionary Computation, CEC 2009
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages70-77
Number of pages8
ISBN (Print)9781424429592
DOIs
Publication statusPublished - 25 Nov 2009
Externally publishedYes
Event2009 IEEE Congress on Evolutionary Computation, CEC 2009 - Trondheim, Norway
Duration: 18 May 200921 May 2009

Publication series

Name2009 IEEE Congress on Evolutionary Computation, CEC 2009

Conference

Conference2009 IEEE Congress on Evolutionary Computation, CEC 2009
CountryNorway
CityTrondheim
Period18/05/0921/05/09

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