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» A fast and elitist multiobjective genetic algorithm: NSGA-II
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76
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TEC
2002
161views more  TEC 2002»
14 years 9 months ago
A fast and elitist multiobjective genetic algorithm: NSGA-II
Multiobjective evolutionary algorithms (EAs) that use nondominated sorting and sharing have been criticized mainly for their: 1) ( 3) computational complexity (where is the number ...
Kalyanmoy Deb, Samir Agrawal, Amrit Pratap, T. Mey...
110
Voted
CEC
2009
IEEE
15 years 2 months ago
Automatic clustering with multi-objective Differential Evolution algorithms
—This paper applies the Differential Evolution (DE) algorithm to the task of automatic fuzzy clustering in a Multi-objective Optimization (MO) framework. It compares the performa...
Kaushik Suresh, Debarati Kundu, Sayan Ghosh, Swaga...
GECCO
2006
Springer
130views Optimization» more  GECCO 2006»
15 years 1 months ago
An efficient multi-objective evolutionary algorithm with steady-state replacement model
The generic Multi-objective Evolutionary Algorithm (MOEA) aims to produce Pareto-front approximations with good convergence and diversity property. To achieve convergence, most mu...
Dipti Srinivasan, Lily Rachmawati
80
Voted
GECCO
2008
Springer
120views Optimization» more  GECCO 2008»
14 years 10 months ago
A robust evolutionary framework for multi-objective optimization
Evolutionary multi-objective optimization (EMO) methodologies, suggested in the beginning of Nineties, focussed on the task of finding a set of well-converged and well-distribute...
Kalyanmoy Deb
PPSN
2004
Springer
15 years 2 months ago
Multi-objective Optimisation by Co-operative Co-evolution
This paper presents the integration between a co-operative co-evolutionary genetic algorithm (CCGA) and four evolutionary multiobjective optimisation algorithms (EMOAs): a multi-ob...
Kuntinee Maneeratana, Kittipong Boonlong, Nachol C...