Indexed by:期刊论文

Date of Publication:2012-10-01

Journal:KOREAN JOURNAL OF CHEMICAL ENGINEERING

Included Journals:SCIE、Scopus

Volume:29

Issue:10

Page Number:1298-1309

ISSN No.:0256-1115

Key Words:Heat Exchanger Network Synthesis; Discrete and Continuous Variables; Genetic Algorithm; Particle Swarm Optimization

Abstract:The heat exchanger network synthesis problem often leads to large-scale non-convex mixed integer nonlinear programming formulations that contain many discrete and continuous variables, as well as nonlinear objective function or nonlinear constraints. In this paper, a novel method consisting of genetic algorithm and particle swarm optimization algorithm is proposed for simultaneous synthesis problem of heat exchanger networks. The simultaneous synthesis problem is solved in the following two levels: in the upper level, the network structures are generated randomly and reproduced using genetic algorithm; and in the lower level, heat load of units and stream-split heat flows are optimized through particle swarm optimization algorithm. The proposed approach is tested on four benchmark problems, and the obtained solutions are compared with those published in previous literature. The results of this study prove that the presented method is effective in obtaining the approximate optimal network with minimum total annual cost as performance index.