A Multi-Swarm Cooperative Perturbed Particle Swarm Optimization
2011 ◽
Vol 225-226
◽
pp. 619-622
Keyword(s):
Combined with a variety of ideas a Multi-swarm cooperative Perturbed Particle Swarm Optimization algorithm (MpPSO) is presented to improve the performance and to reduce the premature convergence of PSO. This algorithm includes the idea of multiple swarms to improve the evolution efficiency by information sharing between populations to avoid falling into local optimum caused by single population. It also includes the idea of perturbing the swarms beside the global best solution, which can escape from local optimum. Experiments show that the proposed algorithm MpPSO has better performance, better convergence and stability when comparing with the traditional and the recently improved particle swarm optimization.
2013 ◽
Vol 760-762
◽
pp. 2194-2198
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2013 ◽
Vol 427-429
◽
pp. 1934-1938
2011 ◽
Vol 308-310
◽
pp. 1099-1105
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2013 ◽
Vol 631-632
◽
pp. 1324-1329
2013 ◽
pp. 31-42
2012 ◽
Vol 532-533
◽
pp. 1664-1669
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2021 ◽
pp. 014233122110295
2011 ◽
Vol 3
(1)
◽
pp. 78-89