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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|Item Type:||Journal Article|
|Keywords:||Exploration and exploitation, particle swarm optimization, search tasking|
|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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