Design Optimization Average-Based Algorithm
Abstract
This article introduces a metaheuristic algorithm to solve engineering design optimization problems. The algorithm is based on the concept of diversity and independence that is aggregated in the average design of a population of designs containing information dispersed through a variety of points, and on the concept of intensification represented by the best design. The algorithm is population-based, where the population individual designs are randomly generated. The population can be normally or uniformly generated. The algorithm may start either with points randomly generated or with a designer preferred trial guess. The algorithm is validated using standard classical unconstrained and constrained engineering optimum design test problems reported in the literature. The results presented indicate that the proposed algorithm is a very simple alternative to solve this kind of problems. They compare well with the analytical solutions and/or the best results achieved so far. Two constrained problem analytical solutions not found in the literature are presented in annex.References
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