An Efficient Coupled Genetic Algorithm-NLP Method for Heat Exchanger Network Synthesis
Document Type: Full article
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.
(2008). An Efficient Coupled Genetic Algorithm-NLP Method for Heat Exchanger Network Synthesis. Iranian Journal of Chemical Engineering(IJChE), 5(1), 22-33.
MLA
. "An Efficient Coupled Genetic Algorithm-NLP Method for Heat Exchanger Network Synthesis". Iranian Journal of Chemical Engineering(IJChE), 5, 1, 2008, 22-33.
HARVARD
(2008). 'An Efficient Coupled Genetic Algorithm-NLP Method for Heat Exchanger Network Synthesis', Iranian Journal of Chemical Engineering(IJChE), 5(1), pp. 22-33.
VANCOUVER
An Efficient Coupled Genetic Algorithm-NLP Method for Heat Exchanger Network Synthesis. Iranian Journal of Chemical Engineering(IJChE), 2008; 5(1): 22-33.
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