A cooperative combinatorial Particle Swarm Optimization algorithm for side-chain packing

TitleA cooperative combinatorial Particle Swarm Optimization algorithm for side-chain packing
Publication TypeConference Papers
Year of Publication2009
AuthorsLapizco-Encinas G, Kingsford C, Reggia JA
Conference NameIEEE Swarm Intelligence Symposium, 2009. SIS '09
Date Published2009/04/30/March
ISBN Number978-1-4244-2762-8
KeywordsAlgorithm design and analysis, Amino acids, combinatorial mathematics, cooperative combinatorial particle swarm optimization algorithm, Design optimization, Encoding, Feedback, numerical optimization, Optimization methods, particle swarm optimisation, Particle swarm optimization, Partitioning algorithms, Proteins, proteomics, proteomics optimization, Robustness, side-chain packing

Particle Swarm Optimization (PSO) is a well-known, competitive technique for numerical optimization with real-parameter representation. This paper introduces CCPSO, a new Cooperative Particle Swarm Optimization algorithm for combinatorial problems. The cooperative strategy is achieved by splitting the candidate solution vector into components, where each component is optimized by a particle. Particles move throughout a continuous space, their movements based on the influences exerted by static particles that then get feedback based on the fitness of the candidate solution. Here, the application of this technique to side-chain packing (a proteomics optimization problem) is investigated. To verify the efficiency of the proposed CCPSO algorithm, we test our algorithm on three side-chain packing problems and compare our results with the provably optimal result. Computational results show that the proposed algorithm is very competitive, obtaining a conformation with an energy value within 1% of the provably optimal solution in many proteins.