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GECCO
2003
Springer
15 years 6 months ago
Generalization of Dominance Relation-Based Replacement Rules for Memetic EMO Algorithms
In this paper, we generalize the replacement rules based on the dominance relation in multiobjective optimization. Ordinary two replacement rules based on the dominance relation ar...
Tadahiko Murata, Shiori Kaige, Hisao Ishibuchi
EMO
2001
Springer
107views Optimization» more  EMO 2001»
15 years 5 months ago
Reducing Local Optima in Single-Objective Problems by Multi-objectivization
One common characterization of how simple hill-climbing optimization methods can fail is that they become trapped in local optima - a state where no small modi cation of the curren...
Joshua D. Knowles, Richard A. Watson, David Corne
GECCO
2007
Springer
200views Optimization» more  GECCO 2007»
15 years 7 months ago
Adaptive variance scaling in continuous multi-objective estimation-of-distribution algorithms
Recent research into single–objective continuous Estimation– of–Distribution Algorithms (EDAs) has shown that when maximum–likelihood estimations are used for parametric d...
Peter A. N. Bosman, Dirk Thierens
GECCO
2007
Springer
148views Optimization» more  GECCO 2007»
15 years 7 months ago
Exploring the behavior of building blocks for multi-objective variation operator design using predator-prey dynamics
In this paper, we utilize a predator-prey model in order to identify characteristics of single-objective variation operators in the multi-objective problem domain. In detail, we a...
Christian Grimme, Joachim Lepping, Alexander Papas...
GECCO
2005
Springer
144views Optimization» more  GECCO 2005»
15 years 6 months ago
Multiobjective hBOA, clustering, and scalability
This paper describes a scalable algorithm for solving multiobjective decomposable problems by combining the hierarchical Bayesian optimization algorithm (hBOA) with the nondominat...
Martin Pelikan, Kumara Sastry, David E. Goldberg