Design optimization with chaos embedded great deluge algorithm

Authors:
Adil Baykasoglu
Affiliations:
Dokuz Eylul University, Faculty of Engineering, Department of Industrial Engineering, 35160 Izmir, Turkey
Venue:
Applied Soft Computing
Year:
2012

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Abstract

In this paper, the great deluge algorithm (GDA), which has not been previously used in constrained mechanical design optimization problems is employed to solve several design optimization problems selected from the literature. The GDA algorithm needs only one basic parameter to setup, which makes it very attractive for solving optimization problems. First time in this paper, an attempt is made to see whether it is possible to enhance the performance of a very simple algorithm like GDA to solve complex constrained non-linear design optimization problems by embedding chaotic maps in its neighborhood generation mechanism. Eight different chaotic maps are tested and compared in this paper. It is observed that chaotic maps can considerably improve the performance of GDA and enables it to find the best possible solutions for the studied problems.