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ISICA
2007
Springer
14 years 2 months ago
A New Evolutionary Decision Theory for Many-Objective Optimization Problems
In this paper the authors point out that the Pareto Optimality is unfair, unreasonable and imperfect for Many-objective Optimization Problems (MOPs) underlying the hypothesis that ...
Zhuo Kang, Lishan Kang, Xiufen Zou, Minzhong Liu, ...
EMO
2009
Springer
140views Optimization» more  EMO 2009»
14 years 1 months ago
On Using Populations of Sets in Multiobjective Optimization
Abstract. Most existing evolutionary approaches to multiobjective optimization aim at finding an appropriate set of compromise solutions, ideally a subset of the Pareto-optimal se...
Johannes Bader, Dimo Brockhoff, Samuel Welten, Eck...
EOR
2006
135views more  EOR 2006»
13 years 8 months ago
Principles of scatter search
Scatter search is an evolutionary method that has been successfully applied to hard optimization problems. The fundamental concepts and principles of the method were first propose...
Rafael Martí, Manuel Laguna, Fred Glover
GECCO
2003
Springer
165views Optimization» more  GECCO 2003»
14 years 1 months ago
An Evolutionary Approach for Molecular Docking
We have developed an evolutionary approach for the flexible docking that is now an important component of a rational drug design. This automatic docking tool, referred to as the G...
Jinn-Moon Yang
CEC
2010
IEEE
13 years 8 months ago
Coevolutionary Temporal Difference Learning for small-board Go
—In this paper we apply Coevolutionary Temporal Difference Learning (CTDL), a hybrid of coevolutionary search and reinforcement learning proposed in our former study, to evolve s...
Krzysztof Krawiec, Marcin Szubert