Abstract
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Article Information:
A Modified Particle Swarm Optimization on Search Tasking
Mohammad Naim Rastgoo, Bahareh Nakisa and Mohammad Ahmadi
Corresponding Author: Mohammad Naim Rastgoo
Submitted: June 08, 2014
Accepted: July 19, 2014
Published: March 15, 2015 |
Abstract:
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Recently, more and more researches have been conducted on the multi-robot system by applying bio- inspired algorithms. Particle Swarm Optimization (PSO) is one of the optimization algorithms that model a set of solutions as a swarm of particles that spread in the search space. This algorithm has solved many optimization problems, but has a defect when it is applied on search tasking. As the time progress, the global searching of PSO decreased and it converged on a small region and cannot search the other region, which is causing the premature convergence problem. In this study we have presented a simulated multi-robot search system to overcome the premature convergence problem. Experimental results show that the proposed algorithm has better performance rather than the basic PSO algorithm on the searching task.
Key words: Multi-robot search system, particle swarm optimization, premature convergence problem , , , ,
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Cite this Reference:
Mohammad Naim Rastgoo, Bahareh Nakisa and Mohammad Ahmadi, . A Modified Particle Swarm Optimization on Search Tasking. Research Journal of Applied Sciences, Engineering and Technology, (8): 594-600.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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