Stratified Sampling Differential Evolution Algorithm for Global Optimization Problem
2012 ◽
Vol 452-453
◽
pp. 1491-1495
Keyword(s):
Differential Evolution (DE) is one kind of evolution algorithm, which based on difference of individuals. DE has exhibited good performance on optimization problem. However, when a local optimal solution is reached with classical Differential Evolution, all individuals in the population gather around it, and escaping from these local optima becomes difficult. To avoid premature convergence of DE, we present in this paper a novel variant of DE algorithm, called SSDE, which uses the stratified sampling method to replace the random sampling method. The proposed SSDE algorithm is compared with some variant DE. The numerical results show that our approach is robust, competitive and fast.
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2015 ◽
Vol 713-715
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pp. 1583-1588
2012 ◽
Vol 452-453
◽
pp. 1491-1495
2019 ◽
Vol 10
(1)
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pp. 1-28
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2010 ◽
Vol 108-111
◽
pp. 328-334
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