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Balancing exploration and exploitation in particle swarm optimization on search tasking

  • Nakisa, Bahareh
  • Rastgoo, Mohammad Naim
  • Norodin, Md. Jan
Publication Date
Sep 25, 2014
Queensland University of Technology ePrints Archive
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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.

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