Heat exchanger networks retrofit with considering pressure drop by coupling genetic algorithm with LP (linear programming) and ILP (integer linear programming) methods

Abstract

This research is trying to develop a new procedure for retrofit of HENs including pressure drop using genetic algorithm (GA) coupled with linear programming (LP) and integer linear programming (ILP) methods. The GA is used to produce structural modifications whereas continuous variables are handled using a converted NLP formulation for Maximum Energy Recovery (MER). The converted NLP consists of an LP for MER with adding a search loop to find the best minimum approach temperature and split ratios which are easier to solve. To prevent complexity and ensure optimum solution, the pressure drops of streams are calculated from the results of LP and then a modified ILP problem is solved to determine the maximum profit of retrofit of HENs. The motivation of the ILP is decision making for elimination or reuse of current exchangers and pumps and/or introducing new ones to the network. Results show that the proposed method often finds better solutions than those reported in the literature.