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» Applying Evolutionary Testing to Search for Critical Defects
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GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
13 years 11 months ago
Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach
This work describes a forward-looking approach for the solution of dynamic (time-changing) problems using evolutionary algorithms. The main idea of the proposed method is to combi...
Iason Hatzakis, David Wallace
GECCO
2007
Springer
186views Optimization» more  GECCO 2007»
14 years 1 months ago
ICSPEA: evolutionary five-axis milling path optimisation
ICSPEA is a novel multi-objective evolutionary algorithm which integrates aspects from the powerful variation operators of the Covariance Matrix Adaptation Evolution Strategy (CMA...
Jörn Mehnen, Rajkumar Roy, Petra Kersting, To...
PPSN
2004
Springer
14 years 22 days ago
SPEA2+: Improving the Performance of the Strength Pareto Evolutionary Algorithm 2
Multi-objective optimization methods are essential to resolve real-world problems as most involve several types of objects. Several multi-objective genetic algorithms have been pro...
Mifa Kim, Tomoyuki Hiroyasu, Mitsunori Miki, Shiny...
GECCO
2006
Springer
185views Optimization» more  GECCO 2006»
13 years 11 months ago
Memory analysis and significance test for agent behaviours
Many agent problems in a grid world have a restricted sensory information and motor actions. The environmental conditions need dynamic processing of internal memory. In this paper...
DaeEun Kim
BIRD
2008
Springer
113views Bioinformatics» more  BIRD 2008»
13 years 9 months ago
Matching Spatial Regions with Combinations of Interacting Gene Expression Patterns
The Edinburgh Mouse Atlas aims to capture in-situ gene expression patterns in a common spatial framework. In this study, we construct a grammar to define spatial regions by combina...
Jano I. van Hemert, Richard A. Baldock