An Agent Based Parallel Particle Swarm Optimization - APPSO
Yann Lorion, Tjorben Bogon, Ingo J. Timm, Oswald Drobnik · 2009
As the complexity of optimization problems increases, new scalable architectures for variable problem complexity are needed. In this paper we introduce an agent based framework for distributing and managing a particle swarm on several interconnected computers. Agent Based Parallel Particle Swarm Optimization (APPSO) accelerates the optimization through parallelization and strategical niching, offers dynamic scalability at runtime, and fault tolerance. Due to its load balancing feature APPSO runs efficient on heterogeneous system. Two experiment series on a prototype implementation demonstrate the performance gain achieved by APPSO.