Adaptive Parent Population Sizing in Evolution Strategies

Author:

LaPorte G. Jake1,Branke Juergen2,Chen Chun-Hung3

Affiliation:

1. Department of Mathematical Sciences, United States Military Academy, West Point, NY 10996, USA

2. Warwick Business School, The University of Warwick, Coventry, CV4 7AL, UK

3. Department of Systems Engineering and Operations Research, George Mason University, Fairfax, VA 22030, USA

Abstract

Adaptive population sizing aims at improving the overall progress of an evolution strategy. At each generation, it determines the parental population size that promises the largest fitness gain, based on the information collected during the evolutionary process. In this paper, we develop an adaptive variant of a [Formula: see text] evolution strategy. Based on considerations on the sphere, we derive two approaches for adaptive population sizing. We then test these approaches empirically on the sphere model using a normalized mutation strength and cumulative mutation strength adaption. Finally, we compare the methodology on more general functions with a fixed population, covariance matrix adaption evolution strategy (CMA-ES). The results confirm that our adaptive population sizing methods yield better results than even the best fixed population size.

Publisher

MIT Press - Journals

Subject

Computational Mathematics

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