TY - Generic T1 - A cooperative combinatorial Particle Swarm Optimization algorithm for side-chain packing T2 - IEEE Swarm Intelligence Symposium, 2009. SIS '09 Y1 - 2009 A1 - Lapizco-Encinas, G. A1 - Kingsford, Carl A1 - Reggia, James A. KW - Algorithm design and analysis KW - Amino acids KW - combinatorial mathematics KW - cooperative combinatorial particle swarm optimization algorithm KW - Design optimization KW - Encoding KW - Feedback KW - numerical optimization KW - Optimization methods KW - particle swarm optimisation KW - Particle swarm optimization KW - Partitioning algorithms KW - Proteins KW - proteomics KW - proteomics optimization KW - Robustness KW - side-chain packing AB - 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. JA - IEEE Swarm Intelligence Symposium, 2009. SIS '09 PB - IEEE SN - 978-1-4244-2762-8 ER -