Particle Swarm Algorithm Based on Boundary Buffering-Natural Evolution and its Application in Constrained Optimization
2014 ◽
Vol 670-671
◽
pp. 1517-1521
Keyword(s):
A particle swarm algorithm (PSO) based on boundary buffering-natural evolution was proposed for solving constrained optimization problems. By buffering the particles that cross boundaries, the diversity of populations was intensified; to accelerate the convergence speed and avoid local optimum of PSO, natural evolution was introduced. In other words, particle hybridization and mutation strategies were applied; and by combining the modified feasible rules, the constrained optimization problems were solved. The simulation results proved that the method was effective in solving this kind of problems.
2013 ◽
Vol 734-737
◽
pp. 2875-2879
2011 ◽
Vol 30
(5)
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pp. 1218-1221
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2012 ◽
Vol 605-607
◽
pp. 2442-2446
2020 ◽
2012 ◽
pp. 545-551
2011 ◽
Vol 10
(8)
◽
pp. 1536-1544
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