A simple distributed particle swarm optimization for dynamic and noisy environments

Xiaohui Cui, Jesse St. Charles, Thomas E. Potok

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Scopus citations

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.

Original languageEnglish
Title of host publicationNature Inspired Cooperative Strategies for Optimization (NICSO 2008)
EditorsKrasnogor Natalio, Maria Belen Melian Batista, Jose Andres Moreno Perez, J. Marcos Moreno-Vega, David Alejandro Pelta
Pages89-102
Number of pages14
DOIs
StatePublished - 2009

Publication series

NameStudies in Computational Intelligence
Volume236
ISSN (Print)1860-949X

Fingerprint

Dive into the research topics of 'A simple distributed particle swarm optimization for dynamic and noisy environments'. Together they form a unique fingerprint.

Cite this