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A Hybrid Discrete Particle Swarm Algorithm for Hard Binary CSPs

  • Qingyun Yang
  • Jigui Sun
  • Juyang Zhang
  • Chunjie Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4222)

Abstract

The discrete particle swarm algorithm for binary constraint satisfaction problems (CSPs) is analyzed in this paper. The analysis denotes that ϕ 1 and ϕ 2 are set to 0 may be a heuristic similar to min-conflict heuristic. The further observation is the impact of local best positions. A control parameter p b is introduced to reduce the effect of the local best positions. To improve the performance, simulated annealing algorithm is combined with the discrete particle swarm algorithm, and the neighborhood exploring in simulated annealing is carried out by ERA model. Eliminating repeated particles and Tabu list avoiding cycling are also introduced in this paper. Our hybrid algorithm is tested with random constraint satisfaction problem instances based on phase transition theory. The experimental results indicate that our hybrid discrete particle swarm algorithm is able to solve hard binary CSPs.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Qingyun Yang
    • 1
    • 2
  • Jigui Sun
    • 1
    • 2
    • 3
  • Juyang Zhang
    • 1
    • 2
  • Chunjie Wang
    • 4
  1. 1.College of Computer Science and TechnologyJilin UniversityChangchunChina
  2. 2.Key Laboratory for Symbolic Computation and Knowledge Engineering of Ministry of EducationJilin UniversityChangchunChina
  3. 3.Open Laboratory for Intelligence Information ProcessingFudan UniversityShanghaiChina
  4. 4.Basic Sciences of ChangChun University of TechnologyChangChun University of TechnologyChangchunChina

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