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» Generalized crowding for genetic algorithms
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ESA
2001
Springer
105views Algorithms» more  ESA 2001»
15 years 2 months ago
SNPs Problems, Complexity, and Algorithms
Abstract. Single nucleotide polymorphisms (SNPs) are the most frequent form of human genetic variation. They are of fundamental importance for a variety of applications including m...
Giuseppe Lancia, Vineet Bafna, Sorin Istrail, Ross...
GECCO
2008
Springer
186views Optimization» more  GECCO 2008»
14 years 10 months ago
A pareto following variation operator for fast-converging multiobjective evolutionary algorithms
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...
A. K. M. Khaled Ahsan Talukder, Michael Kirley, Ra...
GECCO
2005
Springer
159views Optimization» more  GECCO 2005»
15 years 3 months ago
Using evolutionary algorithms for the unit testing of object-oriented software
As the paradigm of object orientation becomes more and more important for modern IT development projects, the demand for an automated test case generation to dynamically test obje...
Stefan Wappler, Frank Lammermann
EH
1999
IEEE
351views Hardware» more  EH 1999»
15 years 2 months ago
Evolvable Hardware or Learning Hardware? Induction of State Machines from Temporal Logic Constraints
Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...
GECCO
2007
Springer
234views Optimization» more  GECCO 2007»
15 years 3 months ago
Applying particle swarm optimization to software testing
Evolutionary structural testing is an approach to automatically generating test cases that achieve high structural code coverage. It typically uses genetic algorithms (GAs) to sea...
Andreas Windisch, Stefan Wappler, Joachim Wegener