4.7 Review

Review of utilization of genetic algorithms in heat transfer problems

Journal

INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
Volume 52, Issue 9-10, Pages 2169-2188

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijheatmasstransfer.2008.11.015

Keywords

Genetic Algorithms (GA); Optimization; Heat transfer; Inverse problems; Design; Correlation; Evolutionary algorithms

Funding

  1. Fonds quebecois de recherche sur la nature et les technologies (FQRNT)
  2. Natural Sciences and Engineering Research Council of Canada (NSERC)

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This review presents when and how Genetic Algorithms (GAs) have been used over the last 15 years in the field of heat transfer. GAs are an optimization tool based on Darwinian evolution. They have been developed in the 1970s, but their utilization in heat transfer problems is more recent. In particular, the last couple of years have seen a sharp increase of interest in GAs for heat transfer related optimization problems. Three main families of heat transfer problems using GAs have been identified: (i) thermal systems design problems, (ii) inverse heat transfer problems, and (iii) development of heat transfer correlations. We present here the main features of the problems addressed with GAs including the modeling, number of variables, and GA settings. This information is useful for future use of GAs in heat transfer. Future possibilities and accomplishments of GAs in heat transfer are also drawn. (C) 2008 Elsevier Ltd. All rights reserved.

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