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An Evolutionary SPDE Breeding-Based Hybrid Particle Swarm Optimizer: Application in Coordination of Robot Ants for Camera Coverage Area Optimization

  • Debraj De
  • Sonai Ray
  • Amit Konar
  • Amita Chatterjee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3776)

Abstract

In this paper we propose a new Hybrid Particle Swarm Optimizer model based on particle swarm, with breeding concepts from novel evolutionary algorithms. The hybrid PSO combines traditional velocity and position update rules of RANDIW-PSO and ideas from Self Adaptive Pareto Differential Evolution Algorithm (SPDE). The hybrid model is tested and compared with some high quality PSO models like the RANDIW-PSO and TVIW-PSO. The results indicate two good prospects of our proposed hybrid PSO model: potential to achieve faster convergence as well as potential to find a better solution. The hybrid PSO model, with the abovementioned features, is then efficiently utilized to coordinate robot ants in order to help them to probe as much camera coverage area of some planetary surface or working field as possible with minimum common area coverage.

Keywords

Particle Swarm Optimization Particle Swarm Hybrid Particle Swarm Optimization Particle Swarm Optimization Model Arithmetic Crossover 
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 2005

Authors and Affiliations

  • Debraj De
    • 1
  • Sonai Ray
    • 1
  • Amit Konar
    • 1
  • Amita Chatterjee
    • 2
  1. 1.Department of Electronics and Telecommunication EngineeringJadavpur UniversityKolkataIndia
  2. 2.Centre of Cognitive ScienceJadavpur UniversityKolkataIndia

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