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GECCO
2003
Springer
15 years 9 months 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
117
Voted
GECCO
2003
Springer
132views Optimization» more  GECCO 2003»
15 years 9 months ago
Circuit Bipartitioning Using Genetic Algorithm
Abstract. In this paper, we propose a hybrid genetic algorithm for partitioning a VLSI circuit graph into two disjoint graphs of minimum cut size. The algorithm includes a local op...
Jong-Pil Kim, Byung Ro Moon
153
Voted
KES
1999
Springer
15 years 8 months ago
Dynamic Demes parallel genetic algorithm
Abstract—Dynamic Demes is a new method for the parallelisation of evolutionary algorithms. It was derived as a combination of two other parallelisation algorithms: the master-sla...
Mariusz Nowostawski, Riccardo Poli
106
Voted
ICPR
2008
IEEE
15 years 10 months ago
Adaptive asymmetrical SVM and genetic algorithms based iris recognition
We propose Genetic Algorithms to improve the feature subset selection by combining the valuable outcomes from multiple feature selection methods. This paper also motivates the use...
Kaushik Roy 0002, Prabir Bhattacharya
ICCTA
2007
IEEE
15 years 10 months ago
Deformation Correction in Brain MRI Using Mutual Information and Genetic Algorithm
During MR imaging, the image of the object may get deformed due to the slope between the MR probe and the object. It is in general undesirable, particularly for 3D imaging. In thi...
Pradipta Maji, Bhabatosh Chanda, Malay Kumar Kundu...