In this paper, echo cancellation is done using genetic algorithm (GA). The genetic algorithm is implemented by two kinds of crossovers; heuristic and microbial. A new procedure is proposed to estimate the coefficients of adaptive filters used in echo cancellation with combination of the GA with Least-Mean-Square (LMS) method. The results are compared for various values of LMS step size and diff...

This paper describes a Genetic Algorithms approach to amanpower-scheduling problem arising at a Petrochemical Company. AlthoughGenetic Algorithms have been successfully used for similar problemsin the past, they always had to overcome the limitations of theclassical Genetic Algorithms paradigm in handling the conflict betweenobjectives and constraints. The approach taken here is to use an indir...

Algorithmic skeleton has received attention as an efficient method of parallel programming in recent years. Using the method, the programmer can implement parallel programs easily. In this study, a set of efficient algorithmic skeletons is introduced for use in implementing parallel genetic algorithm (PGA).A performance modelis derived for each skeleton that makes the comparison of skeletons po...

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...

In this paper, a genetic algorithm is presented for an identical parallel-machine scheduling problem with family setup time that minimizes the total weighted flow time ( ). No set-up is necessary between jobs belonging to the same family. A set-up must be scheduled when switching from the processing of family i jobs to those of another family j, i  j, the duration of this set-up being the sequ...

Today the Genetic Algorithm (GA) is used to solve a large variety of complex nonlinear optimization problems. However, permute convergence which is one of the most important disadvantages in GA is known to increase the number of iterations for reaching a global optimum. This paper, presents a new GA based on chaotic systems to overcome this shortcoming,. We employ logistic map and tent map as t...

Algorithmic skeleton has received attention as an efficient method of parallel programming in recent years. Using the method, the programmer can implement parallel programs easily. In this study, a set of efficient algorithmic skeletons is introduced for use in implementing parallel genetic algorithm (PGA).A performance modelis derived for each skeleton that makes the comparison of skeletons po...

The concepts of robust classification and intelligently controlling the search process of genetic algorithm (GA) are introduced and integrated with a conventional genetic classifier for development of a new version of it, which is called Intelligent and Robust GA-classifier (IRGA-classifier). It can efficiently approximate the decision hyperplanes in the feature space. It is shown experime...