Faculty of Chemical Engineering, Sahand University of Technology, Tabriz, Iran
Abstract
Synthesis of heat exchanger networks (HENs) is inherently a mixed integer andnonlinear programming (MINLP) problem. Solving such problems leads to difficultiesin the optimization of continuous and binary variables. This paper presents a newefficient and robust method in which structural parameters are optimized by geneticalgorithm (G.A.) and continuous variables are handled due to a modified objectivefunction for maximum energy recovery (MER). Node representation is used foraddressing the exchangers and networks are considered as a sequence of genes. Eachgene consists of nodes for generating different structures within a network. Resultsshow that this method may find new or near optimal solutions with a less than 2%increase in Hen annual costs.
Rezaei,E. and Shafiei,S. (2008). An Efficient Coupled Genetic Algorithm-NLP Method for Heat Exchanger Network Synthesis. Iranian Journal of Chemical Engineering (IJChE), 5(1), 22-33.
MLA
Rezaei,E. , and Shafiei,S. . "An Efficient Coupled Genetic Algorithm-NLP Method for Heat Exchanger Network Synthesis", Iranian Journal of Chemical Engineering (IJChE), 5, 1, 2008, 22-33.
HARVARD
Rezaei E., Shafiei S. (2008). 'An Efficient Coupled Genetic Algorithm-NLP Method for Heat Exchanger Network Synthesis', Iranian Journal of Chemical Engineering (IJChE), 5(1), pp. 22-33.
CHICAGO
E. Rezaei and S. Shafiei, "An Efficient Coupled Genetic Algorithm-NLP Method for Heat Exchanger Network Synthesis," Iranian Journal of Chemical Engineering (IJChE), 5 1 (2008): 22-33,
VANCOUVER
Rezaei E., Shafiei S. An Efficient Coupled Genetic Algorithm-NLP Method for Heat Exchanger Network Synthesis. IJChE, 2008; 5(1): 22-33.
