Litcius/Paper detail

Does comma selection help to cope with local optima?

Benjamin Doerr

202030 citationsDOIOpen Access PDF

Abstract

One hope of using non-elitism in evolutionary computation is that it aids leaving local optima. We perform a rigorous runtime analysis of a basic non-elitist evolutionary algorithm (EA), the (μ, λ) EA, on the most basic benchmark function with a local optimum, the jump function. We prove that for all reasonable values of the parameters and the problem, the expected runtime of the (μ, λ) EA is, apart from lower order terms, at least as large as the expected runtime of its elitist counterpart, the (μ + λ) EA (for which we conduct the first runtime analysis to allow this comparison). Consequently, the ability of the (μ, λ) EA to leave local optima to inferior solutions does not lead to a runtime advantage.

Topics & Concepts

Benchmark (surveying)JumpSelection (genetic algorithm)Local optimumComputer scienceComputationEvolutionary algorithmFunction (biology)Mathematical optimizationEvolutionary computationLocal search (optimization)Order (exchange)AlgorithmR packageArtificial intelligenceTheoretical computer scienceMathematicsPopulationEvolutionary Algorithms and ApplicationsMetaheuristic Optimization Algorithms ResearchAdvanced Multi-Objective Optimization Algorithms