Power distribution systems typically have tie and sectionalizing switches whose states determine the topological configuration of the network. The aim of network reconfiguration of the distribution network is to minimize the losses for a load arrangement at a particular time. Thus the objective function is to minimize the losses of the network by satisfying the distribution network constraints....

The main objective of an operative testing strategy is the delivery of a reliable and quality oriented software product to the end user. Testing an application entirely from end to end is a time consuming and laborious process. Exhaustive testing utilizes a good chunk of the resources in a project for meticulous scrutiny to identify even a minor bug. A need to optimize the existing suite is hig...

Multi input multi output (MIMO) radars have multiple antenna radars that each of them can transmit signals. For that matter, to avoid interference, transmitted waveform must be mutually orthogonal. This paper has proposed a new approach by using bee algorithm (BA) and artificial bee colony (ABC) to design orthogonal discrete frequency coding waveforms (DFCWs) which have desirable autocorrelatio...

Segmentation is one of the essential tasks in image processing. Thresholding is one of the simplest techniques for performing image segmentation. Multilevel thresholding is a simple and effective technique. The primary objective of bi-level or multilevel thresholding for image segmentation is to determine a best thresholding value. To achieve multilevel thresholding various techniques has been ...

The artificial bee colony (ABC) algorithm is a swarm-based metaheuristic optimization technique, developed by inspiring foraging and dance behaviors of honey bee colonies. ABC consists of four phases named as initialization, employed bee, onlooker bee and scout bee. The employed bees try to improve their solution in employed bees phase. If an employed bee cannot improve self-solution in a certa...

This research work, proposes an ABC (Artificial Bee Colony Optimization) based framework, motivated by the intelligent behavior of honey bees to automate the test suite optimization process. Here, the bees are implemented as agents that perform the test suite optimization activities seamlessly. Since, the ABC system combines local search methods carried out by employed and onlooker bees with gl...

Cluster examination is data mining task for the assignment of collection a set of items in such a path, to the point that questions in the same gathering (called a cluster) are more like one another than to those in different gatherings (clusters). K-means grouping is a technique for group investigation which intends to parcel n perceptions into k groups in which every perception fits in with t...

Nature is the immense gifted source for solving complex problems. It always helps to find the optimal solution to solve the problem. Mobile Ad Hoc NETwork (MANET) is a wide research area of networks which has set of independent nodes. The characteristics involved in MANET’s are Dynamic, does not depend on any fixed infrastructure or centralized networks, High mobility. The Bio-Inspired algorith...

This paper presents an artificial bee colony (ABC) algorithm for structural optimization of planar and space trusses under stress, displacement and buckling constraints. In order to improve the performance of the classic ABC algorithm, modifications in neighborhood searching method, onlooker phase, and scout phase are proposed. Optimization of different typical truss structures is performed usi...

Artificial bee colony (ABC) algorithm is one of the popular swarm intelligence algorithms. ABC has been developed by being inspired foraging and waggle dance behaviors of real bee colonies in 2005. Since its invention in 2005, many ABC models have been proposed in order to solve different optimization problems. In all the models proposed, there are only one scout bee and a constant limit value ...