Enhancing search space diversity in multi-objective evolutionary drug molecule design using niching

Authors:
Johannes W. Kruisselbrink;Alexander Aleman;Michael T.M. Emmerich;Ad P. IJzerman;Andreas Bender;Thomas Baeck;Eelke van der Horst
Affiliations:
Leiden University, Leiden, Netherlands;Leiden University, Leiden, Netherlands;Leiden University, Leiden, Netherlands;Leiden University, Leiden, Netherlands;Leiden University, Leiden, Netherlands;Leiden University, Leiden, Netherlands;Leiden University, Leiden, Netherlands
Venue:
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Year:
2009

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Abstract

There exist several applications of multi-objective evolutionary algorithms for drug design, however, a common drawback in recent approaches is that the diversity of resulting molecule populations is relatively low. This paper seeks to overcome this problem by introducing niching as a technique to enhance search space diversity. A single population approach with dynamic niche identification is studied in the application domain. In order to apply niching in molecular spaces a metric for measuring the dissimilarity of molecules will be introduced. The approach will be validated in case studies and compared with results of an NSGA-II algorithm without niching in the search space.