Design optimization with chaos embedded great deluge algorithm

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.

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► A novel approach is proposed to solve constrained non-linear mechanical design optimization problems with chaos embedded great deluge algorithm.
► The proposed approach compares several chaotic maps in generating alternative solutions.
► A graph theoretical approach is also proposed to compare alternative chaotic maps which are used within the great deluge algorithm.