2007•Unpublished venueRequires access

A Combined MA-GA Approach for Solving Constrained Optimization Problems

Abu Barkat Ullah, Ruhul Amin Sarker, David J. Cornforth

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.

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Available abstract

Key concepts: Computer science, Mathematical optimization, Benchmark (surveying), Optimization problem, Constrained optimization problem, Test functions for optimization, Constrained optimization, Genetic algorithm