Hybrid Genetic Algorithm (HGA) is a GA that combines quantum operators (rotation, measure, quantum chromosomes, etc.) with classical genetic operators (crossover and mutation).It can be used for the purposes of education and research. HGA is applied in a simple optimization problem:<br><br>Let f(x)=abs(x-5/2+sin(x)) be a function that takes values in the range 0<=x<=15. Within this range f(x) has a maximum value at x=11 (binary value is equal to 1011)
Genetic algorithms, which were created on the basis of observation and imitation of processes happen...
This paper summarizes recent research on heuristic based learning procedures called Genetic Algorith...
Genetic algorithms (GAs) are a class of evolutionary algorithms inspired by Darwinian natural select...
Nowadays genetic algorithm (GA) is greatly used in engineering pedagogy as adaptive technology to le...
. Global Optimization has become an important branch of mathematical analysis and numerical analysis...
Quantum genetic algorithm has the characteristics of good population diversity, rapid convergence an...
This paper introduces first the concept of distance density, and then proposes a new hybrid genetic ...
Sugal is a major new public-domain software package designed to support experimentation with, and im...
Genetic algorithms (GAs) are a class of evolutionary algorithms inspired by Darwinian natural select...
Abstract: Genetic Algorithm (GA) is a calculus free optimization technique based on principles of na...
The Hybrid Genetic Algorithm is developed that out performs a simple genetic algorithm in almost all...
Evolutionary Algorithms started in the 1950's with [Fra57] and [Box57]. They form a powerful fa...
Optimization is a crucial step in the analysis of experimental results. Deterministic methods only c...
Genetic algorithm (GA) is a well known algorithm applied to a wide variety of optimization problems ...
Genetic algorithm (GA) is a well-known population-based optimization algorithm. GA utilizes a random...
Genetic algorithms, which were created on the basis of observation and imitation of processes happen...
This paper summarizes recent research on heuristic based learning procedures called Genetic Algorith...
Genetic algorithms (GAs) are a class of evolutionary algorithms inspired by Darwinian natural select...
Nowadays genetic algorithm (GA) is greatly used in engineering pedagogy as adaptive technology to le...
. Global Optimization has become an important branch of mathematical analysis and numerical analysis...
Quantum genetic algorithm has the characteristics of good population diversity, rapid convergence an...
This paper introduces first the concept of distance density, and then proposes a new hybrid genetic ...
Sugal is a major new public-domain software package designed to support experimentation with, and im...
Genetic algorithms (GAs) are a class of evolutionary algorithms inspired by Darwinian natural select...
Abstract: Genetic Algorithm (GA) is a calculus free optimization technique based on principles of na...
The Hybrid Genetic Algorithm is developed that out performs a simple genetic algorithm in almost all...
Evolutionary Algorithms started in the 1950's with [Fra57] and [Box57]. They form a powerful fa...
Optimization is a crucial step in the analysis of experimental results. Deterministic methods only c...
Genetic algorithm (GA) is a well known algorithm applied to a wide variety of optimization problems ...
Genetic algorithm (GA) is a well-known population-based optimization algorithm. GA utilizes a random...
Genetic algorithms, which were created on the basis of observation and imitation of processes happen...
This paper summarizes recent research on heuristic based learning procedures called Genetic Algorith...
Genetic algorithms (GAs) are a class of evolutionary algorithms inspired by Darwinian natural select...
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