165 search results - page 3 / 33 » On Test Functions for Evolutionary Multi-objective Optimizat... |
HIS
2007
13 years 7 months ago
2007
—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...
GECCO
2007
Springer
13 years 12 months ago
2007
Springer
The resolution of a Multi-Objective Optimization Problem (MOOP) does not end when the Pareto-optimal set is found. In real problems, a single solution must be selected. Ideally, t...
GECCO
2007
Springer
13 years 12 months ago
2007
Springer
There exist a number of high-performance Multi-Objective Evolutionary Algorithms (MOEAs) for solving MultiObjective Optimization (MOO) problems; two of the best are NSGA-II and -M...
GECCO
2007
Springer
13 years 12 months ago
2007
Springer
There has been a considerable body of work on search–based test data generation for branch coverage. However, hitherto, there has been no work on multi–objective branch covera...
GECCO
2005
Springer
13 years 11 months ago
2005
Springer
Various multi–objective evolutionary algorithms (MOEAs) have obtained promising results on various numerical multi– objective optimization problems. The combination with gradi...