Abstract--Most genetic algorithm (GA) users adjust the main parameters of the design of a GA (crossover and mutation probability, population size, number of generations, crossover,...
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...
— In this paper we demonstrate that our ability to match the EXtrinsic Information Transfer (EXIT) function of an Irregular Variable Length Code (IrVLC) to that of a seriallyconc...
Abstract. We present and discuss the results of an experimental analysis in the design of Boolean networks by means of genetic algorithms. A population of networks is evolved with ...
Andrea Roli, Cristian Arcaroli, Marco Lazzarini, S...
Real-world multi-objective engineering design optimization problems often have parameters with uncontrollable variations. The aim of solving such problems is to obtain solutions t...