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» A Multiobjective Frontier Search Algorithm
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GECCO
2008
Springer
124views Optimization» more  GECCO 2008»
13 years 8 months ago
Introducing MONEDA: scalable multiobjective optimization with a neural estimation of distribution algorithm
In this paper we explore the model–building issue of multiobjective optimization estimation of distribution algorithms. We argue that model–building has some characteristics t...
Luis Martí, Jesús García, Ant...
PPSN
2004
Springer
14 years 26 days ago
SPEA2+: Improving the Performance of the Strength Pareto Evolutionary Algorithm 2
Multi-objective optimization methods are essential to resolve real-world problems as most involve several types of objects. Several multi-objective genetic algorithms have been pro...
Mifa Kim, Tomoyuki Hiroyasu, Mitsunori Miki, Shiny...
GECCO
2009
Springer
131views Optimization» more  GECCO 2009»
14 years 3 days ago
Rapid prototyping using evolutionary approaches: part 1
In this paper we describe a multi-objective problem solving approach, simultaneously minimizing average surface roughness Ra and build Time T, for object manufacturing by Rapid Pr...
Nikhil Padhye, Subodh Kalia
EMO
2009
Springer
143views Optimization» more  EMO 2009»
13 years 5 months ago
Adapting to the Habitat: On the Integration of Local Search into the Predator-Prey Model
Traditionally, Predator-Prey Models--although providing a more nature-oriented approach to multi-objective optimization than many other standard Evolutionary Multi-Objective Algori...
Christian Grimme, Joachim Lepping, Alexander Papas...
GECCO
2008
Springer
120views Optimization» more  GECCO 2008»
13 years 8 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