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81
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GECCO
2008
Springer
14 years 11 months ago
2008
Springer
A well-designed fitness function is essential to the effectiveness and efficiency of evolutionary testing. Fitness function design has been researched extensively. For fitness ...
GECCO
2008
Springer
14 years 11 months ago
2008
Springer
In Multi-Objective Problems (MOPs) involving uncertainty, each solution might be associated with a cluster of performances in the objective space depending on the possible scenari...
GECCO
2007
Springer
15 years 4 months ago
2007
Springer
In the design of evolutionary multiobjective optimization (EMO) algorithms, it is important to strike a balance between diversity and convergence. Traditional mask-based crossover...
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GECCO
2006
Springer
15 years 1 months ago
2006
Springer
Evolutionary algorithms have successfully been applied to software testing. Not only approaches that search for numeric test data for procedural test objects have been investigate...
GECCO
2008
Springer
14 years 11 months ago
2008
Springer
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...