Abstract
In this paper, we present a Simple Distributed Particle Swarm Optimization (SDPSO) algorithm that can be used to track the optimal solution in a dynamic and noisy environment. The classic PSO algorithm lacks the ability to track changing optimum in a dynamic environment. Several approaches have been investigated to enhance the PSO algorithm’s ability in dynamic environments. However, in dealing with dynamic environments, these approaches have lost PSO’s original strengths of decentralized control and ease of implementation. The SDPSO algorithm proposed in this paper maintains these classic PSO features as well as provides the optimum result tracking capability in dynamic environments. In this research, the DF1 multimodal dynamic environment generator proposed by Morrison and De Jong is used to evaluate the classic PSO, SDPSO and other two adaptive PSOs.
