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ISDA
2008
IEEE
13 years 11 months ago
Genetic Annealing Optimization: Design and Real World Applications
Both simulated annealing (SA) and the genetic algorithms (GA) are stochastic and derivative-free optimization technique. SA operates on one solution at a time, while the GA mainta...
Mostafa A. El-Hosseini, Aboul Ella Hassanien, Ajit...
EH
2003
IEEE
127views Hardware» more  EH 2003»
13 years 10 months ago
Comparing Different Serial and Parallel Heuristics to Design Combinational Logic Circuits
In this paper, we perform a comparative study of different heuristics used to design combinational logic circuits. The use of local search hybridized with a genetic algorithm and ...
Carlos A. Coello Coello, Enrique Alba, Gabriel Luq...
TEC
2010
132views more  TEC 2010»
12 years 11 months ago
A Hybrid Evolutionary Approach to the Nurse Rostering Problem
Nurse rostering is a difficult search problem with many constraints. In the literature, a number of approaches have been investigated including penalty function methods to tackle t...
Ruibin Bai, Edmund K. Burke, Graham Kendall, Jingp...
CPHYSICS
2006
127views more  CPHYSICS 2006»
13 years 5 months ago
GenAnneal: Genetically modified Simulated Annealing
A modification of the standard Simulated Annealing (SA) algorithm is presented for finding the global minimum of a continuous multidimensional, multimodal function. We report resu...
Ioannis G. Tsoulos, Isaac E. Lagaris
ADMA
2005
Springer
189views Data Mining» more  ADMA 2005»
13 years 10 months ago
Parallel Genetic Algorithm and Parallel Simulated Annealing Algorithm for the Closest String Problem
In this paper, we design genetic algorithm and simulated annealing algorithm and their parallel versions to solve the Closest String problem. Our implementation and experiments sho...
Xuan Liu, Hongmei He, Ondrej Sýkora