Sciweavers

473 search results - page 17 / 95
» Rank based variation operators for genetic algorithms
Sort
View
IJCAI
2007
13 years 9 months ago
Adaptive Genetic Algorithm with Mutation and Crossover Matrices
A matrix formulation for an adaptive genetic algorithm is developed using mutation matrix and crossover matrix. Selection, mutation, and crossover are all parameter-free in the se...
Nga Lam Law, Kwok Yip Szeto
ISDA
2008
IEEE
14 years 2 months ago
Cultural-Based Genetic Algorithm: Design and Real World Applications
Due to their excellent performance in solving combinatorial optimization problems, metaheuristics algorithms such as Genetic Algorithms (GA), Simulated Annealing (SA) and Tabu Sea...
Mostafa A. El-Hosseini, Aboul Ella Hassanien, Ajit...
CEC
2005
IEEE
13 years 9 months ago
Population based incremental learning with guided mutation versus genetic algorithms: iterated prisoners dilemma
Axelrod’s original experiments for evolving IPD player strategies involved the use of a basic GA. In this paper we examine how well a simple GA performs against the more recent P...
Timothy Gosling, Nanlin Jin, Edward P. K. Tsang
GECCO
2008
Springer
158views Optimization» more  GECCO 2008»
13 years 8 months ago
Convergence analysis of quantum-inspired genetic algorithms with the population of a single individual
In this paper, the Quantum-inspired Genetic Algorithms with the population of a single individual are formalized by a Markov chain model using a single and the stored best individ...
Mehrshad Khosraviani, Saadat Pour-Mozafari, Mohamm...
EPS
1997
Springer
13 years 11 months ago
An Individually Variable Mutation-Rate Strategy for Genetic Algorithms
Abstract. In Neo-Darwinism, mutation can be considered to be unaffected by selection pressure. This is the metaphor generally used by the genetic algorithm for its treatment of the...
Stephen A. Stanhope, Jason M. Daida