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GEOINFORMATICA
2002
92views more  GEOINFORMATICA 2002»
13 years 7 months ago
Using Genetic Algorithms for Solving Hard Problems in GIS
Genetic algorithms (GAs) are powerful combinatorial optimizers that are able to
Steven van Dijk, Dirk Thierens, Mark de Berg
GECCO
2008
Springer
238views Optimization» more  GECCO 2008»
13 years 8 months ago
Using multiple offspring sampling to guide genetic algorithms to solve permutation problems
The correct choice of an evolutionary algorithm, a genetic representation for the problem being solved (as well as their associated variation operators) and the appropriate values...
Antonio LaTorre, José Manuel Peña, V...
GECCO
2006
Springer
166views Optimization» more  GECCO 2006»
13 years 11 months ago
Solving identification problem for asynchronous finite state machines using genetic algorithms
A Genetic Algorithm, embedded in a simulation-based method, is applied to the identification of Asynchronous Finite State Machines. Two different coding schemes and their associat...
Xiaojun Geng
GECCO
1999
Springer
158views Optimization» more  GECCO 1999»
13 years 11 months ago
Coevolutionary Genetic Algorithms for Solving Dynamic Constraint Satisfaction Problems
In this paper, we discuss the adaptability of Coevolutionary Genetic Algorithms on dynamic environments. Our CGA consists of two populations: solution-level one and schema-level o...
Hisashi Handa, Osamu Katai, Tadataka Konishi, Mits...
GECCO
2003
Springer
14 years 21 days ago
A Kernighan-Lin Local Improvement Heuristic That Solves Some Hard Problems in Genetic Algorithms
We present a Kernighan-Lin style local improvement heuristic for genetic algorithms. We analyze the run-time cost of the heuristic. We demonstrate through experiments that the heur...
William A. Greene