[PDF] Top 20 Optimization with Quantum Genetic Algorithm

... of quantum computing with the prin- ciples of genetic algorithm is still a promising research ...of quantum comput- ...that quantum rotation gates are updated us- ing the quantum ... See full document

... Quantum genetic algorithms have a wide range of ...the quantum genetic algorithm to the cloud computing job ...chain quantum genetic algorithm (ADCQGA) for solving ... See full document

... Design optimization is performed by nonlinear programming ...implemented Genetic Algorithm for solving the design optimization problem of Cantilever beam and Torsion ...cross-section ... See full document

... a quantum algorithm to exactly solve certain problems in combinatorial optimization, including weighted MAX-2-SAT as well as problems where the objective function is a weighted sum of products of ... See full document

... Genetic algorithm (GA) is a search algorithm based on the behavior of natural selection and ...three genetic operators: selection, crossover and ...main genetic operator and consists of ... See full document

... Genetic Algorithm is a metaheuristic strategy use to solve combinatorial and hard optimization problem, It starts by generating an initial population of individual (solution) of some finite size, the ... See full document

... hybrid optimization algorithm based Genetic Algorithms (GAs) is proposed to solve constrained optimization engineering ...hybrid Genetic Algorithms (GA) and great deluge ... See full document

... a genetic algorithm with evolutionary ...showing optimization of Bipod micro (2 DOF), uses the robust nature of the genetic algorithm and applies it to the multi-criteria ... See full document

... network optimization, the optimal robust solution of hub-spoke network is obtained under the condition of multiple possibilities of demand and cost, and an optimization method based on multi-objective ... See full document

... multi-objective optimization problems: such as Ant Colony algorithm, COA (Cuckoo Algorithm, Genetic algorithm, particle swarm optimization algorithm, fuzzy ... See full document

... decades, genetic algorithm (GA), particle swarm optimization (PSO), ant colony optimization (ACO), Artificial Fish School Algorithm, Bacteria Foraging Optimization ... See full document

... phase shifter using a pair of multi-section radial transmission-line (TL) stubs is proposed in [3]. Global optimization is performed using the TL model followed by a local optimization based on a more ... See full document

... meta-heuristic algorithm to solve the Markowitz model has attracted more and more researchers' ...fireworks algorithm, to solve the mean-VaR/CVaR model, experiment results show that fireworks ... See full document

... the Genetic algorithm and Particle swarm ...evolutionary algorithm required a fitness function which is to be minimized and the authors who uses genetic algorithm tried to develop a ... See full document

... convex optimization with constraints in this paper, which is proved to be ...Swarm Optimization (PSO) and Genetic Algorithm (GA) is ...of genetic algorithm and the local optimum ... See full document

... cost optimization of concrete structures given by Sarma and Adeli [14], demonstrated that most papers face up to structural optimization interested of weight ...cost optimization mainly were devoted ... See full document

... of optimization problems which can't be solved easily by using the conventional ...namely, Genetic Algorithm(GA), Cuckoo Search(CS), Particle Swarm Optimization(PSO) and Ant Colony ... See full document

... the optimization of complex systems and drug discov- ...of quantum computing technology on theo- retical/applicative aspects of computation as well as on the society in the next decades is considered to be ... See full document

... the algorithm. Commonly, the algorithm terminates when either a maximum number of generations has been produced, or a satisfactory fitness level has been reached for the ...the algorithm has ... See full document

... sections, genetic algorithms, ant colony optimization, particle swarm optimization, simulat- ed annealing, differential evolution, and teaching-learn- ing-based optimization, and the ... See full document