A generalized method for HEN synthesis using stochastic optimization - II. The synthesis of cost-optimal networks

This paper presents a generalized method for the synthesis of heat-exchanger networks (HENs) based on genetic algorithms (GAs). This approach is a modification of the algorithm presented in the first part of this paper, which was limited to MILP formulations. Since the aim of this study is to obtain a family of cost-optimum HENs in which stream splitting is supported, both the objective function and the constraints are non-linear. An automated procedure is used to formulate a constrained non-linear optimization model, whose solution provides a measure of the fitness of each candidate HEN generated by the CA. A novel algorithm is proposed for the solution of the NLP, which exploits the observation that optimal designs usually involve relatively few stream splits, and that the NLP constraints are linear in the heat duties. The NLP is solved using a cascaded algorithm involving an upper-level non-linear optimization of the stream split flows, and a lower-level pseudo-linear optimization of the heat exchanger duties. The performance of the proposed approach is demonstrated using several medium-scale case studies, and the obtained solutions are compared with those available in literature. (C) 1998 Elsevier Science Ltd. All rights reserved.