In a recent paper [1], it was shown that a new Genetic Algorithm (GA) performed better than basic GA. In the present paper, we will focus an Improved Genetic Algorithm which uses the theory of cosets. The new technique was tested using some benchmark functions [2] which the basic GA performance was not good enough. The main purpose of this paper is to suggest how to use Linear Codes properties ...

We use genetic algorithms (GAs) to nd good nite horizon policies for POMDPs, where the search is limited to policies with a xed nite amount of policy memory. Initial results were presented in (Lusena et al. 1999) with one GA. In this paper, diierent cross-over and mutation rates are compared. Initializing the population of the genetic algorithm is done using smaller genetic algorithms. The sele...

in this paper, the gain in ld-celp speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (pso) algorithms to optimize the structure and parameters of neural networks. elman, multi-layer perceptron (mlp) and fuzzy artmap are the candidate neural models. the optimized number of nodes in the first and second hidden layers of el...

The current study presents an improved genetic algorithm(GA) for the flexible job shop scheduling problem (FJSP). The coding is divided into working sequence level and machine level and two effective crossover operators and mutation operators are designed for the generation and reduce the disruptive effects of genetic operators. The algorithm is tested on instances of 10 working sequences and 1...

Obtaining accurate predictions of unobserved genetic or phenotypic values for complex traits in animal, plant, and human populations is possible through whole-genome prediction (WGP), a combined analysis of genotypic and phenotypic data. Because the underlying genetic architecture of the trait of interest is an important factor affecting model selection, we propose a new strategy, termed BLUP|G...

if both reference station (rs) and navigational device in differential global positioning system (dgps) receive signals from the same satellite, rs position components error (rpce) can be used to compensate for navigational device error. this research used hybrid method for rpce prediction which was collected by a low-cost gps receiver. it is a combination of genetic algorithm (ga) computing an...

In optimization problem, Genetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO) have been known as good alternative techniques. GA is designed by adopting the natural evolution process, while ACO is inspired by the foraging behaviour of ant species. This paper presents a hybrid GA-ACO for Travelling Salesman Problem (TSP), called Genetic Ant Colony Optimization (GACO). In this metho...