A new multi-objective particle swarm optimization algorithm using clustering applied to automated docking

Authors:
Stefan Janson;Daniel Merkle
Affiliations:
Department of Computer Science, University of Leipzig, Leipzig, Germany;Department of Computer Science, University of Leipzig, Leipzig, Germany
Venue:
HM'05 Proceedings of the Second international conference on Hybrid Metaheuristics
Year:
2005

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Abstract

In this paper we introduce the new hybrid Particle Swarm Optimization algorithm for multi-objective optimization ClustMPSO. We combined the PSO algorithm with clustering techniques to divide all particles into several subswarms. Strategies for updating the personal best position of a particle, for selection of the neighbourhood best and for swarm dominance are proposed. The algorithm is analyzed on both artificial optimization functions and on an important real world problem from biochemistry. The molecule docking problem is to predict the three dimensional structure and the affinity of a binding of a target receptor and a ligand. ClustMPSO clearly outperforms a well-known Lamarckian Genetic Algorithm for the problem.