Balancing exploration and exploitation in particle swarm optimization on search tasking


Autoria(s): Nakisa, Bahareh; Rastgoo, Mohammad Naim; Norodin, Md. Jan
Data(s)

25/09/2014

Resumo

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.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/86089/

Publicador

Maxwell Science Publications

Relação

http://eprints.qut.edu.au/86089/1/v8-1429-1434%20%282%29.pdf

http://maxwellsci.com/print/rjaset/v8-1429-1434.pdf

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.

Direitos

© Maxwell Scientific Organization, 2014

Fonte

School of Information Systems; Science & Engineering Faculty

Palavras-Chave #Exploration and exploitation #particle swarm optimization #search tasking
Tipo

Journal Article