So many techniques are used in the software testing environment and in this paper we survey the ABC algorithmic approach and its advantages over the GA (Genetic Algorithms). Artificial bee colony (ABC) algorithm is one of the most recently introduced swarm–based algorithms. These optimization approaches helps in memorization and also support the global optima. This algorithm is based on colony ...

In this paper, the performances of the Artificial Bee Colony (ABC) Algorithm and Invasive Weed Optimization (IWO) Algorithm are compared on the basis of modified versions of five well known benchmark functions. The modifications are performed on these functions in order to get rid of the symmetrical properties of the selected functions. Further a solution space is shifted so that the optimal fu...

In this paper we present a modification of artificial bee colony (ABC) algorithm for constrained optimization problems. In nature more than one onlooker bee goes to a promising food source reported by employed bee. Our proposed modification forms a mutant solution in onlooker phase using three onlookers. This approach obtains better results than the original artificial bee colony algorithm. Our...

Artificial Bee Colony (ABC) optimization algorithm is a swarm intelligence based nature inspired algorithm which has been proved a competitive algorithm with some popular nature-inspired algorithms. However, it is found that the ABC algorithm prefers exploration at the cost of the exploitation. Therefore, in this paper a self adaptive fitness based mutation strategy is presented in which the pe...

This paper presents a hybrid clustering algorithm and feed-forward neural network classifier for land-cover mapping of trees, shade, building and road. It starts with the single step preprocessing procedure to make the image suitable for segmentation. The pre-processed image is segmented using the hybrid geneticArtificial Bee Colony(ABC) algorithm that is developed by hybridizing the ABC and ge...

The solution accuracy of economic dispatch problems is associated with the accuracy of the fuel cost curve parameters. Therefore, updating of these parameters is a very important issue to further improve the final accuracy of economic dispatch problems. Estimating the parameters of the fuel cost curve may be the best solution for this issue. This paper presents an application of the artificial ...

Image segmentation of pulmonary parenchyma can be detected from multisliced CT images using image segmentation. It can be modeled as a nonlinear multimodal global optimization problem. The traditional 2D Otsu algorithm, though effective, is quite time consuming for determining the optimum threshold values. In this paper we propose a combination of 2D Otsu method with modified ABC algorithm (cal...

Approximate Bayesian computation (ABC) methods can be used to evaluate posterior distributions without having to calculate likelihoods. In this paper, we discuss and apply an ABC method based on sequential Monte Carlo (SMC) to estimate parameters of dynamical models. We show that ABC SMC provides information about the inferability of parameters and model sensitivity to changes in parameters, an...

Artificial bee colony (ABC) algorithm has been introduced recently for solving optimization problems. The ABC algorithm is based on intelligent foraging behavior of honeybee swarms and has many advantages over earlier swarm intelligence algorithms. In this work, a new method based on ABC algorithm for designing two-channel quadrature mirror filter (QMF) banks with linear phase is presented. To ...

Sudoku is a popular newspaper puzzle that has become an international phenomenon. Sudoku which means “single digits” is a logicbased combinatorial puzzle with rules that are quite simple. Several algorithms have been used to solve this combinatorial optimization problem. This paper explores the possibility of using the Artificial Bee Colony (ABC) algorithm, a relatively new swarm-based optimiza...