GAHC
swMATH ID:  2734 
Software Authors:  Matousek, Radomil 
Description:  This paper introduces a novel improved evolutionary algorithm, which combines genetic algorithms and hill climbing. Genetic Algorithms (GA) belong to a class of well established optimization metaheuristics and their behavior are studied and analyzed in great detail. Various modifications were proposed by different researchers, for example modifications to the mutation operator. These modifications usually change the overall behavior of the algorithm. This paper presents a binary GA with a modified mutation operator, which is based on the wellknown Hill Climbing Algorithm (HCA). The resulting algorithm, referred to as GAHC, also uses an elite tournament selection operator. This selection operator preserves the best individual from the GA population during the selection process while maintaining the positive characteristics of the standard tournament selection. This paper discusses the GAHC algorithm and compares its performance wit! h standard GA. 
Homepage:  http://www.springerlink.com/content/t1q3560850kn1704/fulltext.pdf 
Programming Languages:  None 
Operating Systems:  None 
Dependencies:  None 
Keywords:  genetic algorithm; HC mutation; hill climbing algorithm 
Related Software:  HC12; Simulink; MersenneTwister; COINOR; CONOPT; Matlab; BARON 
Cited in:  5 Publications 
Standard Articles
1 Publication describing the Software, including 1 Publication in zbMATH  Year 

GAHC: Hybrid genetic algorithm. Zbl 1160.68509 Matousek, Radomil 
2009

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top 5
Cited by 10 Authors
3  Matousek, Radomil 
2  Senkerik, Roman 
1  Chadli, Mohammed 
1  Davendra, Donald 
1  Lampinen, Jouni A. 
1  Minar, Petr 
1  Oplatkova, Zuzana Kominkova 
1  Pluhacek, Michal 
1  Žampachová, Eva 
1  Zelinka, Ivan 
Cited in 1 Serial
1  Optimization Methods & Software 
Cited in 5 Fields
2  Computer science (68XX) 
2  Systems theory; control (93XX) 
1  Dynamical systems and ergodic theory (37XX) 
1  Statistics (62XX) 
1  Operations research, mathematical programming (90XX) 