Comparative study of NSGA-Ⅱ and NSGA-Ⅲ on multi-objective optimization of heat exchanger network

被引：0

作者：

Jiang, Ning ^{[1
]}

Fan, Wei ^{[1
]}

Xie, Xiaodong ^{[1
]}

Guo, Fengyuan ^{[1
]}

Li, Enteng ^{[1
]}

Zhao, Shichao ^{[1
]}

机构：

[1] College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou,Zhejiang,310023, China

来源：

Huagong Jinzhan/Chemical Industry and Engineering Progress | 2020年 / 39卷 / 07期

关键词：

Heat exchangers - Multiobjective optimization - Specific heat;

D O I：

10.16085/j.issn.1000-6613.2019-1466

中图分类号：

学科分类号：

摘要：

For the widely used multi-objective genetic algorithms, NSGA-Ⅱ and NSGA-Ⅲ, this paper combines the specific heat exchanger network retrofit problems to compare the performance of the two algorithms. The case study results showed that the NSGA-Ⅱ is more efficient than the NSGA-Ⅲ, especially under the condition of large population, and the running time of NSGA-Ⅲ is above 2 times that of NSGA-Ⅱ. The application of NSGA-Ⅱ algorithm is not strictly limited by the maximum target number of three. NSGA-Ⅱ may also have good performance when solving multi-objective optimization problems with more than 3 targets. The number of targets is not the strict standard of selecting NSGA-Ⅱ or NSGA-Ⅲ algorithm. The NSGA-Ⅱ algorithm is more likely to obtain the extreme value of each target from the single performance index of the heat exchanger network in the 10H×5C heat exchanger network case including four related targets. From the index of the minimum total annual cost, the optimal schemes of the two algorithms are similar. In the 7H×3C heat exchanger network optimization including six targets, the NSGA-Ⅲ algorithm obtains better target extreme values. From the index of the minimum annual cost, the capital cost and annual total cost by the NSGA-Ⅲ algorithm are smaller. Therefore, for multi-objective optimization problems with no more than 3 objective functions or more than 3 related objective functions, it is recommended to use the NSGA-Ⅱ algorithm to achieve fast optimization. The NSGA-Ⅲ algorithm is based on the reference point-based selection mechanism, so its calculation efficiency is slower, and it is more suitable for high-dimensional multi-objective optimization problems with difficulty in convergence. © 2020, Chemical Industry Press. All right reserved.

引用

页码：2534 / 2547