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145
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EMO
2009
Springer
155views Optimization» more  EMO 2009»
15 years 10 months ago
An Improved Version of Volume Dominance for Multi-Objective Optimisation
Abstract. This paper proposes an improved version of volume dominance to assign fitness to solutions in Pareto-based multi-objective optimisation. The impact of this revised volum...
Khoi Le, Dario Landa Silva, Hui Li
153
Voted
IJCNN
2006
IEEE
15 years 9 months ago
Generalization Improvement in Multi-Objective Learning
— Several heuristic methods have been suggested for improving the generalization capability in neural network learning, most of which are concerned with a single-objective (SO) l...
Lars Gräning, Yaochu Jin, Bernhard Sendhoff
126
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CEC
2007
IEEE
15 years 10 months ago
SAT-decoding in evolutionary algorithms for discrete constrained optimization problems
— For complex optimization problems, several population-based heuristics like Multi-Objective Evolutionary Algorithms have been developed. These algorithms are aiming to deliver ...
Martin Lukasiewycz, Michael Glaß, Christian ...
114
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GECCO
2006
Springer
179views Optimization» more  GECCO 2006»
15 years 7 months ago
Comparison of multi-objective evolutionary algorithms in optimizing combinations of reinsurance contracts
Our paper concerns optimal combinations of different types of reinsurance contracts. We introduce a novel approach based on the Mean-Variance-Criterion to solve this task. Two sta...
Ingo Oesterreicher, Andreas Mitschele, Frank Schlo...
149
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HIS
2007
15 years 5 months ago
Pareto-based Multi-Objective Machine Learning
—Machine learning is inherently a multiobjective task. Traditionally, however, either only one of the objectives is adopted as the cost function or multiple objectives are aggreg...
Yaochu Jin