Balancing exploration and exploitation in particle swarm optimization on search tasking

Nakisa, Bahareh, Rastgoo, Mohammad Naim, & Norodin, Md. Jan (2014) Balancing exploration and exploitation in particle swarm optimization on search tasking. Research Journal of Applied Sciences, Engineering and Technology, 8(12), pp. 1429-1434.

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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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ID Code: 86089
Item Type: Journal Article
Refereed: Yes
Additional URLs:
Keywords: Exploration and exploitation, particle swarm optimization, search tasking
ISSN: 2040-7467
Divisions: Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: © Maxwell Scientific Organization, 2014
Deposited On: 29 Jul 2015 23:16
Last Modified: 31 Jul 2015 00:23

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