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For genetic algorithms, there are many strategies to choose individuals: general, and elitist. The general approach is the simplest approach, in which the algorithm replaces the whole current population by the offspring generated so far. In the elitist strategy, parents and offspring compete for survival. With the elitist approach, only the best individuals are selected from the current generation. In this article, we compare the results of the non-elitist genetic algorithm, and the elitist genetic algorithm improved with the parenting fitness. Results show that the elitist genetic algorithm improved with parenting fitness outperforms the non-elitist one in 93% cases.

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A Comparison Between the (μ+ λ) and (μ, λ) Genetic Algorithm

  • 会议论文

  • 发表日期：

    2026年

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  • Mustapha Ouiss,
  • Abdelaziz Ettaoufik,
  • Abdelaziz Marzak

摘要

For genetic algorithms, there are many strategies to choose individuals: general, and elitist. The general approach is the simplest approach, in which the algorithm replaces the whole current population by the offspring generated so far. In the elitist strategy, parents and offspring compete for survival. With the elitist approach, only the best individuals are selected from the current generation. In this article, we compare the results of the non-elitist genetic algorithm, and the elitist genetic algorithm improved with the parenting fitness. Results show that the elitist genetic algorithm improved with parenting fitness outperforms the non-elitist one in 93% cases.