A Simple Distributed Particle Swarm Optimization for Dynamic and Noisy Environments

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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 ... continued below

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Cui, Xiaohui & Potok, Thomas E January 1, 2009.

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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.

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  • Report No.: None
  • Grant Number: DE-AC05-00OR22725
  • Office of Scientific & Technical Information Report Number: 1038489
  • Archival Resource Key: ark:/67531/metadc831682

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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  • January 1, 2009

Added to The UNT Digital Library

  • May 19, 2016, 3:16 p.m.

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  • Dec. 7, 2016, 9:13 p.m.

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Cui, Xiaohui & Potok, Thomas E. A Simple Distributed Particle Swarm Optimization for Dynamic and Noisy Environments, book, January 1, 2009; Berlin, Germany. (digital.library.unt.edu/ark:/67531/metadc831682/: accessed November 22, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.