A cooperative particle swarm optimizer with migration of heterogeneous probabilistic models View Full Text


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Article Info

DATE

2010-03

AUTHORS

Mohammed El-Abd, Mohamed S. Kamel

ABSTRACT

Particle Swarm Optimization (PSO) is a stochastic optimization approach that originated from simulations of bird flocking, and that has been successfully used in many applications as an optimization tool. Estimation of distribution algorithms (EDAs) are a class of evolutionary algorithms which perform a two-step process: building a probabilistic model from which good solutions may be generated and then using this model to generate new individuals. Two distinct research trends that emerged in the past few years are the hybridization of PSO and EDA algorithms and the parallelization of EDAs to exploit the idea of exchanging the probabilistic model information. In this work, we propose the use of a cooperative PSO/EDA algorithm based on the exchange of heterogeneous probabilistic models. The model is heterogeneous because the cooperating PSO/EDA algorithms use different methods to sample the search space. Three different exchange approaches are tested and compared in this work. In all these approaches, the amount of information exchanged is adapted based on the performance of the two cooperating swarms. The performance of the cooperative model is compared to the existing state-of-the-art PSO cooperative approaches using a suite of well-known benchmark optimization functions. More... »

PAGES

57-89

References to SciGraph publications

  • 2004. Migration of Probability Models Instead of Individuals: An Alternative When Applying the Island Model to EDAs in PARALLEL PROBLEM SOLVING FROM NATURE - PPSN VIII
  • 1998. Telephone network traffic overloading diagnosis and evolutionary computation techniques in ARTIFICIAL EVOLUTION
  • 2004. Multiple-Deme Parallel Estimation of Distribution Algorithms: Basic Framework and Application in PARALLEL PROCESSING AND APPLIED MATHEMATICS
  • 2009-06. Performance evaluation of TRIBES, an adaptive particle swarm optimization algorithm in SWARM INTELLIGENCE
  • 2006. Ant Colony Optimization in METAHEURISTIC PROCEDURES FOR TRAINING NEUTRAL NETWORKS
  • 2006. An Estimation of Distribution Particle Swarm Optimization Algorithm in ANT COLONY OPTIMIZATION AND SWARM INTELLIGENCE
  • 1998. Extending population-based incremental learning to continuous search spaces in PARALLEL PROBLEM SOLVING FROM NATURE — PPSN V
  • 2006. A Parallel Island Model for Estimation of Distribution Algorithms in TOWARDS A NEW EVOLUTIONARY COMPUTATION
  • 2003. Distributed Probabilistic Model-Building Genetic Algorithm in GENETIC AND EVOLUTIONARY COMPUTATION — GECCO 2003
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s11721-009-0037-5

    DOI

    http://dx.doi.org/10.1007/s11721-009-0037-5

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1006399381


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