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GECCO
2006
Springer
179views Optimization» more  GECCO 2006»
15 years 1 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...
IJCNN
2006
IEEE
15 years 3 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
VLSID
2006
IEEE
112views VLSI» more  VLSID 2006»
15 years 3 months ago
Handling Constraints in Multi-Objective GA for Embedded System Design
Design space exploration is central to embedded system design. Typically this is a multi-objective search problem, where performance, power, area etc. are the different optimizati...
Biman Chakraborty, Ting Chen, Tulika Mitra, Abhik ...
EVOW
2006
Springer
15 years 1 months ago
Mining Structural Databases: An Evolutionary Multi-Objetive Conceptual Clustering Methodology
Abstract. The increased availability of biological databases containing representations of complex objects permits access to vast amounts of data. In spite of the recent renewed in...
Rocío Romero-Záliz, Cristina Rubio-E...
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
15 years 2 months ago
TestFul: using a hybrid evolutionary algorithm for testing stateful systems
This paper introduces TestFul, a framework for testing stateful systems and focuses on object-oriented software. TestFul employs a hybrid multi-objective evolutionary algorithm, t...
Matteo Miraz, Pier Luca Lanzi, Luciano Baresi