An Efficient Coupled Genetic Algorithm-NLP Method for Heat Exchanger Network Synthesis

نویسندگان: ثبت نشده
چکیده مقاله:

Synthesis of heat exchanger networks (HENs) is inherently a mixed integer and nonlinear programming (MINLP) problem. Solving such problems leads to difficulties in the optimization of continuous and binary variables. This paper presents a new efficient and robust method in which structural parameters are optimized by genetic algorithm (G.A.) and continuous variables are handled due to a modified objective function for maximum energy recovery (MER). Node representation is used for addressing the exchangers and networks are considered as a sequence of genes. Each gene consists of nodes for generating different structures within a network. Results show that this method may find new or near optimal solutions with a less than 2% increase in Hen annual costs.

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عنوان ژورنال

دوره 5  شماره 1

صفحات  22- 33

تاریخ انتشار 2008-01-01

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