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GECCO
2007
Springer
156views Optimization» more  GECCO 2007»
13 years 11 months ago
Techniques for highly multiobjective optimisation: some nondominated points are better than others
The research area of evolutionary multiobjective optimization (EMO) is reaching better understandings of the properties and capabilities of EMO algorithms, and accumulating much e...
David W. Corne, Joshua D. Knowles
GECCO
2008
Springer
124views Optimization» more  GECCO 2008»
13 years 6 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...
CEC
2010
IEEE
13 years 6 months ago
Evolutionary multi-objective optimization algorithms with probabilistic representation based on pheromone trails
Abstract-- Recently, the research on quantum-inspired evolutionary algorithms (QEA) has attracted some attention in the area of evolutionary computation. QEA use a probabilistic re...
Hui Li, Dario Landa Silva, Xavier Gandibleux
PATAT
2004
Springer
141views Education» more  PATAT 2004»
13 years 10 months ago
A Hybrid Multi-objective Evolutionary Algorithm for the Uncapacitated Exam Proximity Problem
A hybrid Multi-Objective Evolutionary Algorithm is used to tackle the uncapacitated exam proximity problem. In this hybridization, local search operators are used instead of the tr...
Pascal Côté, Tony Wong, Robert Sabour...
GECCO
2007
Springer
157views Optimization» more  GECCO 2007»
13 years 11 months ago
Global multiobjective optimization via estimation of distribution algorithm with biased initialization and crossover
Multiobjective optimization problems with many local Pareto fronts is a big challenge to evolutionary algorithms. In this paper, two operators, biased initialization and biased cr...
Aimin Zhou, Qingfu Zhang, Yaochu Jin, Bernhard Sen...