This paper presents a novel approach for the synthesis of heat-exchanger networks (HENs) based on genetic algorithms (GAs). The use of the algorithm is demonstrated on the solution of relatively simple HEN synthesis problems in which maximum energy recovery (MER) is desired and which can be resolved without resorting to stream splitting. As a result, the parametric optimization problem is an LP. The problem is solved in two parts : (a) the structure of the HEN is determined by GAs, and (b) the heat loads of units are fixed by the Simplex algorithm to meet MER which is used by the GAs to rate fitness. A physically meaningful HEN structure representation is proposed which can be both effectively manipulated by genetic operators and is also appropriate for parametric optimization by the Simplex algorithm. The approach is demonstrated on several case studies, and the obtained solutions are compared with those which have appeared in the literature. The second part of this paper uses essentially the same framework to tackle the general HEN synthesis problem in which an arbitrarily non-linear objective function can be optimized, and in which the constraints can also be non-linear. (C) 1998 Elsevier Science Ltd. All rights reserved.