Improving NSGA-II for solving multi objective function optimization problems

It is important for any MOEA (Multi Objective Evolutionary Algorithm) to improve convergence and diversity of solutions of Pareto front, which is obtained at the termination of MOEA. There are many MOEA available in the literature: NSGA-II, SPEA, SPEA2, PESAII and IBEA. This paper aims at improving...

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Veröffentlicht in:	2016 International Conference on Computer Communication and Informatics (ICCCI) S. 1 - 6
Hauptverfasser:	Vachhani, Vimal L., Dabhi, Vipul K., Prajapati, Harshadkumar B.
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.01.2016
Schlagworte:	Clustering algorithms Clustering methods Convergence Diversity Diversity methods MOEA Multi-objective Optimization Non- domination NSGA-II Optimization Sociology Statistics
ISBN:	9781467366793, 146736679X
Online-Zugang:	Volltext
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