Network Design Problem Using Genetic Algorithm-an Empirical Study on Mutation Operator
نویسندگان
چکیده
منابع مشابه
Genetic Algorithm for Network Design Problem-An Empirical Study of Crossover Operator with Generation and Population Variation
This paper presents an influence of genetic operators (crossover) in genetic algorithm for network design problem. It also describes the performance variation with the number of generation and number of chromosomes for various different sizes of networks. A network design problem for this paper falls under the network topology category which is a degree constrained minimum spanning tree with va...
متن کاملSolving Travelling Salesman Problem Using Genetic Algorithm Based on Heuristic Crossover and Mutation Operator
Genetic Algorithm (GAs) is used to solve optimization problems. It is depended on the selection operator, crossover and mutation rates. In this paper Roulette Wheel Selection (RWS) operator with different crossover and mutation probabilities, is used to solve well known optimization problem Traveling Salesmen Problem (TSP). We have compared the results of RWS with another selection method Stoch...
متن کاملWireless sensor network design through genetic algorithm
In this paper, we study WSN design, as a multi-objective optimization problem using GA technique. We study the effects of GA parameters including population size, selection and crossover method and mutation probability on the design. Choosing suitable parameters is a trade-off between different network criteria and characteristics. Type of deployment, effect of network size, radio communication...
متن کاملSTRUCTURAL OPTIMIZATION USING A MUTATION-BASED GENETIC ALGORITHM
The present study is an attempt to propose a mutation-based real-coded genetic algorithm (MBRCGA) for sizing and layout optimization of planar and spatial truss structures. The Gaussian mutation operator is used to create the reproduction operators. An adaptive tournament selection mechanism in combination with adaptive Gaussian mutation operators are proposed to achieve an effective search in ...
متن کاملReal-Coded Gentic Algorithm using Bayesian Network as Genetic Operator
In this paper, we propose, Gaussian Optimization Algorithm (GOA), which generate a new search point by using gaussian network and estimation of distribution. Algorithms where offsprings (new search points) are generated according to estimated probability model of the parents are called Estimation of Distribution Algorithms (DEAs) or Probabilistic Model-Building GAs (PMBGAs). The proposed GOA is...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Soft Computing
سال: 2010
ISSN: 1816-9503
DOI: 10.3923/ijscomp.2010.171.176