The Improved NSGA - II Based on Reverse Learning Mechanism
Authors
Qiong Yuan, Guangming Dai
Corresponding Author
Qiong Yuan
Available Online March 2015.
- DOI
- 10.2991/iiicec-15.2015.135How to use a DOI?
- Keywords
- Multi-objective optimization; The NSGA-II algorithm;Reverse learning mechanism
- Abstract
In this paper,According to the shortages of the NSGA - II algorithm in terms of the simulated binary crossover (SBX) operator , the speed of convergence and the diversity performance,The reverse learning mechanism (RLM) is applied to the initialization and evolutionary process of the NSGA-II,And introducing an improved arithmetic crossover operator.Through the series of ZDT test functions in two aspects of convergence and diversity evaluation it show that the improved NSGA - II algorithm on the convergence speed, convergence and diversity is better than the NSGA - II algorithm.
- Copyright
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Qiong Yuan AU - Guangming Dai PY - 2015/03 DA - 2015/03 TI - The Improved NSGA - II Based on Reverse Learning Mechanism BT - Proceedings of the 2015 International Industrial Informatics and Computer Engineering Conference PB - Atlantis Press SP - 589 EP - 593 SN - 2352-538X UR - https://doi.org/10.2991/iiicec-15.2015.135 DO - 10.2991/iiicec-15.2015.135 ID - Yuan2015/03 ER -