Balancing exploration and exploitation in particle swarm optimization on search tasking

Bahareh Nakisa, Mohammad Naim Rastgoo, Md Jan Norodin

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

In this study we present a combinatorial optimization method based on particle swarm optimization and local search algorithm on the multi-robot search system. Under this method, in order to create a balance between exploration and exploitation and guarantee the global convergence, at each iteration step if the distance between target and the robot become less than specific measure then a local search algorithm is performed. The local search encourages the particle to explore the local region beyond to reach the target in lesser search time. Experimental results obtained in a simulated environment show that biological and sociological inspiration could be useful to meet the challenges of robotic applications that can be described as optimization problems.

Original languageEnglish
Pages (from-to)1429-1434
Number of pages6
JournalResearch Journal of Applied Sciences, Engineering and Technology
Volume8
Issue number12
DOIs
Publication statusPublished - 1 Jan 2014

Fingerprint

Particle swarm optimization (PSO)
Robots
Combinatorial optimization
Robotics
Local search (optimization)

Keywords

  • Exploration and exploitation
  • local search algorithm
  • particle swarm optimization
  • search tasking

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

Cite this

Balancing exploration and exploitation in particle swarm optimization on search tasking. / Nakisa, Bahareh; Rastgoo, Mohammad Naim; Norodin, Md Jan.

In: Research Journal of Applied Sciences, Engineering and Technology, Vol. 8, No. 12, 01.01.2014, p. 1429-1434.

Research output: Contribution to journalArticle

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