Comparison between the Performance of GA and PSO in Structural Optimization Problems
Journal Title: American journal of Engineering Research - Year 2016, Vol 5, Issue 11
Abstract
Genetic Algorithms and Particle Swarm Optimization are two of the most popular heuristic optimization techniques. They belong to the same group of population-based methods and are often regarded as competitors. While there have been previous attempts to compare the two, both methods performances depend heavily on the selection of their parameters. This paper presents a study in which the critical parameters are varied for both techniques and only the best performing sets are compared. The optimization problem chosen as the comparison framework is a benchmark problem in the structural optimization field. The results show that the Genetic Algorithms are generally better than the Particle Swarm Optimization with regard to all performance indicators.
Authors and Affiliations
Razvan Cazacu1
Keywords
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