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Volume 18, Issue 3
Fall 2010
Issue Cover
All Issues
ISSN 1063-6560
EISSN 1530-9304
In this Issue
Editorial for the Special Issue on Theoretical Aspects of Evolutionary Multi-Objective Optimization
Thomas Jansen, Frank Neumann
Evolutionary Computation (2010) 18 (3): 333–334.
View articletitled, Editorial for the Special Issue on Theoretical Aspects of Evolutionary Multi-Objective Optimization
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On the Effect of Populations in Evolutionary Multi-Objective Optimisation
Oliver Giel, Per Kristian Lehre
Evolutionary Computation (2010) 18 (3): 335–356.
View articletitled, On the Effect of Populations in Evolutionary Multi-Objective Optimisation
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Exploring the Runtime of an Evolutionary Algorithm for the Multi-Objective Shortest Path Problem
Christian Horoba
Evolutionary Computation (2010) 18 (3): 357–381.
View articletitled, Exploring the Runtime of an Evolutionary Algorithm for the Multi-Objective Shortest Path Problem
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An Efficient Algorithm for Computing Hypervolume Contributions
Karl Bringmann, Tobias Friedrich
Evolutionary Computation (2010) 18 (3): 383–402.
View articletitled, An Efficient Algorithm for Computing Hypervolume Contributions
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An Efficient and Accurate Solution Methodology for Bilevel Multi-Objective Programming Problems Using a Hybrid Evolutionary-Local-Search Algorithm
Kalyanmoy Deb, Ankur Sinha
Evolutionary Computation (2010) 18 (3): 403–449.
View articletitled, An Efficient and Accurate Solution Methodology for Bilevel Multi-Objective Programming Problems Using a Hybrid Evolutionary-Local-Search Algorithm
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Regular Papers

A New Method for Modeling the Behavior of Finite Population Evolutionary Algorithms
Tatsuya Motoki
Evolutionary Computation (2010) 18 (3): 451–489.
View articletitled, A New Method for Modeling the Behavior of Finite Population Evolutionary Algorithms
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Self-Adaptation of Mutation Operator and Probability for Permutation Representations in Genetic Algorithms
Martin Serpell, James E. Smith
Evolutionary Computation (2010) 18 (3): 491–514.
View articletitled, Self-Adaptation of Mutation Operator and Probability for Permutation Representations in Genetic Algorithms
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