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An Efficient Coupled Genetic Algorithm-Nlp Method For Heat Exchanger Network Synthesis.
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نویسنده
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Rezaei E. ,Shafiei S.
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منبع
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Iranian Journal Of Chemical Engineering - 2008 - دوره : 5 - شماره : 1 - صفحه:22 -33
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چکیده
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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 objectivefunction 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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کلیدواژه
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Heat Exchanger Networks (Hens) ,Optimization ,Genetic Algorithm (G.A.) ,Nlp Formulation.
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آدرس
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Sahand University Of Technology, Faculty Of Chemical Engineering , ایران, Sahand University Of Technology, Faculty Of Chemical Engineering , ایران
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پست الکترونیکی
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e_rezaei@sut.ac.ir
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Authors
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