Parallel Hybrid PSO-GA Algorithm and Its Application to Layout Design

  • Guangqiang Li
  • Fengqiang Zhao
  • Chen Guo
  • Hongfei Teng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4221)


Packing and layout problems belong to NP-Complete problems theoretically and have found a wide utilization in practice. Parallel genetic algorithms (PGA) are relatively effective to solve these problems. But there still exist some defects of them, e.g. premature convergence and slow convergence rate. To overcome them, a parallel hybrid PSO-GA algorithm (PHPSO-GA) is proposed based on PGA. In PHPSO-GA, subpopulations are classified as several classes according to probability values of improved adaptive crossover and mutation operators. And in accordance with characteristics of different classes of subpopulations, different modes of PSO update operators are introduced. It aims at making full use of the fast convergence property of particle swarm optimization. Adjustable arithmetic-progression rank-based selection is introduced into this algorithm as well. It not only can prevent the algorithm from premature in the early stage of evolution but also can accelerate convergence rate in the late stage of evolution. To be hybridized with simplex method can improve local search performance. An example of layout design problem shows that PHPSO-GA is feasible and effective.


Particle Swarm Optimization Layout Design Layout Problem Parallel Genetic Algo Slow Convergence Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Guangqiang Li
    • 1
  • Fengqiang Zhao
    • 2
  • Chen Guo
    • 1
  • Hongfei Teng
    • 3
  1. 1.College of Automation and Electrical EngineeringDalian Maritime UniversityDalianPeople’s Republic of China
  2. 2.College of Electromechanical & Information EngineeringDalian Nationalities UniversityDalianPeople’s Republic of China
  3. 3.School of Mechanical EngineeringDalian University of TechnologyDalianPeople’s Republic of China

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