A Comparative Analysis of Genetic Algorithm Replacement Strategies in a Real-World Optimization Problem: An Elitism and Diversity Oriented Perspective
DOI:
https://doi.org/10.64470/elene.2025.1002Keywords:
Genetic Algorithm, Replacement Strategy, Elitism, Diversity, Selective Harmonic Elimination, Multilevel InverterAbstract
In this study, generation replacement strategies used in genetic algorithms are comparatively analysed in the context of a real-world optimization problem, with a focus on the balance between elitism and diversity. The problem under consideration involves solving the equations of the Selective Harmonic Elimination (SHE) method, which is widely used for controlling Multilevel Inverters (MLIs). Six algorithms, each employing a different replacement mechanism, were tested under four distinct scenarios composed of various population sizes and iteration counts. The results were evaluated using fundamental statistical metrics, boxplots, and convergence curves. The findings reveal that elitist strategies perform better in large-population, long-duration scenarios, whereas approaches prioritizing diversity yield more effective results under limited resource conditions. This study systematically demonstrates the impact of different replacement strategies on optimization performance and offers valuable insights for strategy selection in real-world optimization problems
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