The Improved NSGA - II Based on Reverse Learning Mechanism

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/).

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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  -