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 -