Divergence of character and premature convergence: a survey of methodologies for promoting diversity in evolutionary optimization

Giovanni Squillero (1) , Alberto Tonda (2)

1 DAUIN Dipartimento di Automatica e Informatica
2 GMPA - Génie et Microbiologie des Procédés Alimentaires

In the past decades, different evolutionary optimization methodologies have been proposed by scholars and exploited by practitioners, in a wide range of applications. Each paradigm shows distinctive features, typical advantages, and characteristic disadvantages; however, one single problem is shared by almost all of them: the "lack of speciation". While natural selection favors variations toward greater divergence, in artificial evolution candidate solutions do homologize. Many authors argued that promoting diversity would be beneficial in evolutionary optimization processes, and that it could help avoiding premature convergence on suboptimal solutions. The paper surveys the research in this area up to mid 2010s, it re-orders and re-interprets different methodologies into a single framework, and proposes a novel three-axis taxonomy. Its goal is to provide the reader with a unifying view of the many contributions in this important corpus, allowing comparisons and informed choices. Characteristics of the different techniques are discussed, and similarities are highlighted; practical ways to measure and promote diversity are also suggested. (C) 2015 Elsevier Inc. All rights reserved.

Mots clés: Evolutionary optimization; Diversity preservation

Domaines: Sciences du Vivant [q-bio]

Giovanni Squillero, Alberto Tonda. Divergence of character and premature convergence: a survey of methodologies for promoting diversity in evolutionary optimization. Information Sciences, 2016, 329, pp.782-799. ⟨10.1016/j.ins.2015.09.056⟩. ⟨hal-01531616⟩