Dynamic Heterogeneous Particle Swarm Optimization

Hierarchical Heterogeneous Particle Swarm Optimization

Particle swarm optimization (PSO) has recently been modified to several versions. Heterogeneous PSO is a recent extension which includes behavioral heterogeneity of particles. Here we propose a further developed version that has hierarchical interaction patterns among heterogeneous particles, which we call hierarchical heterogeneous PSO (HHPSO). Two algorithm designs that have been developed an...

Dynamic Sociometry in Particle Swarm Optimization

The performance of Particle Swarm Optimization is greatly affected by the size and sociometry of the swarm. This research proposes a dynamic sociometry, which is shown to be more effective on some problems than the standard star and ring sociometries. The performance of various combinations of swarm size and sociometry on six different test functions is qualitatively analyzed.

Particle Swarm Optimization in Dynamic Environments

Unified Particle Swarm Optimization in Dynamic Environments

A first investigation of the recently proposed Unified Particle Swarm Optimization algorithm on dynamic environments is provided and discussed on widely used test problems. Results are very promising compared to the corresponding results of the standard Particle Swarm Optimization algorithm, indicating the superiority of the new scheme.

Compound Particle Swarm Optimization in Dynamic Environments

Adaptation to dynamic optimization problems is currently receiving a growing interest as one of the most important applications of evolutionary algorithms. In this paper, a compound particle swarm optimization (CPSO) is proposed as a new variant of particle swarm optimization to enhance its performance in dynamic environments. Within CPSO, compound particles are constructed as a novel type of p...