Optimal design of plate-fin heat exchangers by a hybrid evolutionary algorithm

This study explores the first application of a Genetic Algorithm hybrid with Particle Swarm Optimization (GAHPSO) for design optimization of a plate-fin heat exchanger. A total number of seven design parameters are considered as the optimization variables and the constraints are handled by penalty f...

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Bibliographic Details
Main Authors: Yousefi, Moslem, Enayatifar, Rasul, Darus, Amer Nordin
Format: Article
Published: Elsevier Ltd. 2012
Subjects:
Online Access:http://eprints.utm.my/id/eprint/47312/
http://dx.doi.org/10.1016/j.icheatmasstransfer.2011.11.011
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Summary:This study explores the first application of a Genetic Algorithm hybrid with Particle Swarm Optimization (GAHPSO) for design optimization of a plate-fin heat exchanger. A total number of seven design parameters are considered as the optimization variables and the constraints are handled by penalty function method. The effectiveness and accuracy of the proposed algorithm is demonstrated through an illustrative example. Comparing the results with the corresponding results using GA and PSO reveals that the GAHPSO can converge to optimum solution with higher accuracy.