Sciweavers

54 search results - page 7 / 11
» Privacy-Preserving Multi-Objective Evolutionary Algorithms
Sort
View
142
Voted
EMO
2009
Springer
143views Optimization» more  EMO 2009»
15 years 11 days ago
Adapting to the Habitat: On the Integration of Local Search into the Predator-Prey Model
Traditionally, Predator-Prey Models--although providing a more nature-oriented approach to multi-objective optimization than many other standard Evolutionary Multi-Objective Algori...
Christian Grimme, Joachim Lepping, Alexander Papas...
124
Voted
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
15 years 7 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
121
Voted
CEC
2007
IEEE
15 years 9 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 ...
116
Voted
GECCO
2007
Springer
185views Optimization» more  GECCO 2007»
15 years 8 months ago
SNDL-MOEA: stored non-domination level MOEA
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...
Matt D. Johnson, Daniel R. Tauritz, Ralph W. Wilke...
125
Voted
ICST
2010
IEEE
15 years 1 months ago
TestFul: An Evolutionary Test Approach for Java
Abstract—This paper presents TestFul, an evolutionary testing approach for Java classes that works both at class and method level. TestFul exploits a multi-objective evolutionary...
Luciano Baresi, Pier Luca Lanzi, Matteo Miraz