Particle Swarm Optimization for energy minimization of molecular systems

The minimization of a potential energy function can be used to provide insight into the ground state configuration of a wide range of molecular systems. Optimization problems of this type can be challenging for deterministic (e.g. line search) optimization algorithms due to the size of the search space and the large number of local minima that are inherent within molecular configuration problems. We describe how Particle Swarm Optimization, a stochastic optimization algorithm inspired by flocking behavior, can be used to accurately and efficiently solve energy minimization problems associated with molecular systems.