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» A fast and elitist multiobjective genetic algorithm: NSGA-II
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TEC
2002
161views more  TEC 2002»
13 years 4 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...
CEC
2009
IEEE
13 years 9 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»
13 years 8 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
GECCO
2008
Springer
120views Optimization» more  GECCO 2008»
13 years 6 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
13 years 10 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...