A Study of Archiving Strategies in Multi-objective PSO for Molecular Docking

  • José García-NietoEmail author
  • Esteban López-CamachoEmail author
  • María Jesús García GodoyEmail author
  • Antonio J. NebroEmail author
  • Juan J. DurilloEmail author
  • José F. Aldana-MontesEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9882)


Molecular docking is a complex optimization problem aimed at predicting the position of a ligand molecule in the active site of a receptor with the lowest binding energy. This problem can be formulated as a bi-objective optimization problem by minimizing the binding energy and the Root Mean Square Deviation (RMSD) difference in the coordinates of ligands. In this context, the SMPSO multi-objective swarm-intelligence algorithm has shown a remarkable performance. SMPSO is characterized by having an external archive used to store the non-dominated solutions and also as the basis of the leader selection strategy. In this paper, we analyze several SMPSO variants based on different archiving strategies in the scope of a benchmark of molecular docking instances. Our study reveals that the SMPSOhv, which uses an hypervolume contribution based archive, shows the overall best performance.


Multi-objective optimization Particle Swarm Optimization Molecular docking Archiving strategies Algorithm comparison 



This work is partially funded by Grants TIN2011-25840 (Ministerio de Ciencia e Innovación) and P11-TIC-7529 and P12-TIC-1519 (Plan Andaluz I+D+I). This article is based upon work from COST Action CA15140, supported by COST (European Cooperation in Science and Technology).


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Khaos Research Group, Department of Computer SciencesUniversity of Málaga, ETSI InformáticaMálagaSpain
  2. 2.Distributed and Parallel Systems GroupUniversity of InnsbruckInnsbruckAustria

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