Two Multi-Objective Genetic Algorithms for Finding Optimum Design of an I-beam

Ali Khazaee, Hossein Miar Naimi

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DOI: 10.4236/eng.2011.310131                

Abstract

Many engineering design problems are characterized by presence of several conflicting objectives. This requires efficient search of the feasible design region for optimal solutions which simultaneously satisfy multiple design objectives. Genetic algorithm optimization (GAO) is a powerful search technique with faster convergence rates than traditional evolutionary algorithms. This paper applies two GAO-based approaches to multi-objective engineering design and finds design variables through the feasible space. To demonstrate the utility of the proposed methods, the multi-objective design of an I-beam will be presented.

Keywords

Genetic Algorithm, Multi-Objective, I-Beam, Optimization

Conflicts of Interest

The authors declare no conflicts of interest.

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