Comparison of Coding Methods for a Genetic Algorithm in Multi-objective Optimization of an Indeterminate Structure

Rahat SULTANA, Wendy REFFEOR, Shabbir CHOUDHURI

Abstract


Two different coding algorithms are used to find optimal support locations for an indeterminate structure using a Genetic Algorithm. The objective is to equalize the load distribution among the supports while maximizing the enclosed polygonal area by the supports to increase stability of the structure. In the first approach, called the continuous method, the candidate surface for the support locations was used as a continuum of space. In the second approach, called the discretized method, the solution space is broken into rectangular grids and the index number of the nodal points are used as genes in coding the problem. The average value of the objective function in the discretized method is found to be 0.0147 compared to the average value of 0.405 in the continuous method. The discretized method also outperformed the continuous method in each component of the multi-objective problem and showed faster convergence towards the optima.

Keywords


Coding algorithm in a GA, Multi-objective optimization using GA, Indeterminate Structure.


DOI
10.12783/dtetr/icamm2016/7337

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