Genetic Algorithms in Problem Solving
An Innovative Genetic Algorithms Based Inexact Non Linear Programming Problem Solving Method
... The approach of operational programming with inexact analysis often treats the uncertain parameters as intervals with known lower and upper bounds and un- clear distributions. A major advantage of inexact programming is ...
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Genetic Algorithms Dynamic Population Size with Cloning in Solving Traveling Salesman Problem
... saw-tooth genetic algorithm combining the effects of variable population size and reinitialization to enhance ...Evolutionary algorithms with on-thefly population size adjustment. Parallel Problem ...
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Cheating for problem solving: a genetic algorithm with social interactions
... As already mentioned, we assume a mixed population composed by two kinds of chromosomes: cooperators and defectors. The cooperators correspond to the usual GA chromosomes, whose fitness is calculated in conformity with ...
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No Fit Polygon for Nesting Problem Solving with Hybridizing Ant Algorithms
... nesting problem is NP-hard, while pheromone evaporation is the process concerning the pheromone trail intensity on the components decreases over ...the genetic algorithms use an adaptive fitness ...
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Solving the graph coloring problem via hybrid genetic algorithms
... NP-complete and that the determination of the chromatic number v(G) is NP-hard ( Garey and Johnson, 1979 ). There- fore several methods and heuristics have been proposed to solve this problem. The first used ...
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Solving Poisson Equation by Genetic Algorithms
... Encoding Method: the ordinal encoding scheme was used in the proposed method. Under this scheme, a serial number is assigned to each gene from 0 to s where s=50. Initial population size: generally, the initial population ...
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Using Genetic Algorithms for Solving the Comparison Based Identification Problem of Multifactor Estimation Model
... for solving the comparison-based structure-parametric identification prob- lem of multifactor estimation model are ...with genetic algo- rithms is proposed to solve the ...of genetic ...
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Solving ISP Problem by Using Genetic Algorithm
... problems. Genetic algorithms have been successfully applied to many different types of problems, though several factors limit the success of a GA on a specific ...function. Problem required are good, ...
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Improvements on Heuristic Algorithms for Solving Traveling Salesman Problem
... The difference between metaheuristic and hyperheuristic is lie actually on the solution space of the problem. Both of these approaches search the solution heuristically but the solution spaces are different. ...
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New Approach for Solving Dynamic Traveling Salesman Problem with Hybrid Genetic Algorithms and Ant Colony Optimization
... Hybrid algorithms are part of these ...hybrid algorithms, initial answers of ACO among the obtained data from routes for the mutations are selected by ...
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Parallel Genetic Algorithms for University Scheduling Problem
... for solving the university timetabling problem, mainly due to the emergence of multi core ...roulette genetic algorithms: one based on islands and the other one on threads, to improve solution ...
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Review of Traveling Salesman Problem for the genetic algorithms
... Keywords: Genetic algorithms; TSP; crossover; mutation; ...Introduction Genetic Algorithm is an optimization technique based on natural evolution that includes the idea of surviving of the most ...
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Heuristic Algorithms for Solving Bounded Diameter Minimum Spanning Tree Problem and Its Application to Genetic Algorithm Development
... This problem is known to be NP-hard for 4 ≤ k < |V|-1 ...heuristic algorithms for solving BDMST: OTTC (Abdall, 2001), RGH ...proposed algorithms, we apply them for initializing the population ...
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Solving Vehicle Routing Problem with Proposed Non Dominated Sorting Genetic Algorithm and Comparison with Classical Evolutionary Algorithms
... optimization problem at hand. Multi-objective genetic algorithm (MOGA) being a population-based approach, genetic algorithm (GA) are suited to solve multi-objective optimization problems [11, ...
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Solving a Stochastic Cellular Manufacturing Model by Using Genetic Algorithms
... Base of genetic algorithms (GAs) in natural evolution studies the transformation of the organism type for more adaptation to its environment. In spite of other stochastic search methods, GAs searches the ...
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Genetic Algorithms for Solving Disjoint PathProblem with Proportional Path-Costs
... phenotype space is one to one. This helps avoid unnecessary evaluations, resulting in a more effective genetic search. Legality requires all encoded individuals in genotype to correspond to a solution for the ...
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A rectification strategy in genetic algorithms for academic timetabling problem
... first problem instance Figure 4 Fitness progression for the second problem instance Figure 5 Fitness progression for the third problem instance It is evident that the algorithm which features the ...
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Solving Travelling Salesman Problem with an Improved Hybrid Genetic Algorithm
... hybrid genetic algorithm to solve the two-dimensional Euc- lidean traveling salesman problem (TSP), in which the crossover operator is en- hanced with a local ...hybrid genetic algorithm outperforms ...
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An Enriched Adaptive Genetic Algorithm for Solving Reactive Power Problem
... adaptive genetic algorithm, probability of crossover, probability of mutation, reactive power ...dispatch problem is one of the difficult optimization problems in power ...The problem that has to be ...
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Solving travelling salesman problem with an improved hybrid genetic algorithm.
... in solving TSP, such as Genetic Algorithm (GA) [2] [3], Simulated Annealing (SA) [4], Ant Colony Optimization (ACO) [5], Particle Swarm Optimization (PSO) [6], Tabu Search (TS) [7], Neural Net- work (NN) ...
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