Adaptive competitive swarm optimization for heat exchanger networks without split streams

被引：0

作者：

Chen S. ^{[1
]}

Luo N. ^{[1
]}

机构：

[1] Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai

来源：

Luo, Na (naluo@ecust.edu.cn) | 1600年 / Materials China卷 / 67期

基金：

中国国家自然科学基金; 上海市自然科学基金;

关键词：

Adaptive; Competitive swarm optimization; Heat exchanger network; MINLP; Optimization;

D O I：

10.11949/j.issn.0438-1157.20160581

中图分类号：

学科分类号：

摘要：

For large-scale super-structure optimization on non-convex and non-linear heat exchanger network, conventional intelligent optimization algorithms have poor efficiency and easily fall into local optima. Adaptive competitive swarm optimization algorithm was proposed to optimize no-split stream heat exchanger networks with targeted total annual cost. This method improved abilities of both global and local optimization by attenuated learning of average particle positions and self-adaptive adjusting on weight average of speed. Simulation on two typical cases showed that the proposed algorithm sharply reduced cycles of model being used, shortened optimization time and achieved better optimization results in comparison with quantum particle swarm algorithm. © All Right Reserved.

引用

页码：4716 / 4723

页数：7