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

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.