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144
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PPSN
2004
Springer
15 years 11 months ago
Exploring the Evolutionary Details of a Feasible-Infeasible Two-Population GA
Abstract. A two-population Genetic Algorithm for constrained optimization is exercised and analyzed. One population consists of feasible candidate solutions evolving toward optimal...
Steven Orla Kimbrough, Ming Lu, David Harlan Wood
IJCAI
1993
15 years 7 months ago
Evolutionary Learning Strategy using Bug-Based Search
We introduce a new approach to GA (Genetic Algorithms) based problem solving. Earlier GAs did not contain local search (i.e. hill climbing) mechanisms, which led to optimization d...
Hitoshi Iba, Tetsuya Higuchi, Hugo de Garis, Taisu...
143
Voted
GECCO
2005
Springer
163views Optimization» more  GECCO 2005»
15 years 12 months ago
Benefits of software measures for evolutionary white-box testing
White-box testing is an important method for the early detection of errors during software development. In this process test case generation plays a crucial role, defining appropr...
Frank Lammermann, Stefan Wappler
WWW
2003
ACM
16 years 7 months ago
An Evolutionary Approach to Web Request Prediction
This paper proposes an evolutionary algorithm that evolves a population of finite state automata to exploit user navigational path behavior to predict, in real-time, future reques...
Dario Bonino, Fulvio Corno, Giovanni Squillero
CIKM
2007
Springer
16 years 16 days ago
Randomized metric induction and evolutionary conceptual clustering for semantic knowledge bases
We present an evolutionary clustering method which can be applied to multi-relational knowledge bases storing resource annotations expressed in the standard languages for the Sema...
Nicola Fanizzi, Claudia d'Amato, Floriana Esposito