Hybrid evolutionary programming for heavily constrained problems

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A hybrid of evolutionary programming (EP) and a deterministic optimization procedure is applied to a series of nonlinear and quadratic optimization problems. The hybrid scheme is compared with other existing schemes such as EP alone, two-phase (TP) optimization, and EP with a non-stationary penalty function (NS-EP). The results indicate that the hybrid method can outperform the other methods when addressing heavily constrained optimization problems in terms of computational efficiency and solution accuracy.
Publisher
ELSEVIER SCI IRELAND LTD
Issue Date
1996
Language
English
Article Type
Article
Keywords

NEURAL NETWORKS; OPTIMIZATION

Citation

BIOSYSTEMS, v.38, no.1, pp.29 - 43

ISSN
0303-2647
URI
http://hdl.handle.net/10203/73038
Appears in Collection
EE-Journal Papers(저널논문)
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