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...

Artificial bee colony is a population-based search algorithm that mimics a natural behavior of real honey bees to find rich food sources to obtain maximum quantity of nectar and share the information of food sources with other bees in the hive. This paper concerns primarily about how to use artificial bee colony to solve examination timetabling problems which it is known as a NP-hard problem. I...

An approach for quick assessment of the exposure to ergonomic risks on computer-aided office workplaces in a company is developed. It includes a checklist considering the following ergonomic dimensions: work organization, displays, input devices, furniture, work space, environment, software and health hazards. By the checklist, data on workplace exposure to ergonomic risk factors are collected....

One of the essential parts of the software development process is software testing as it ensures the delivery of a good quality and reliable software. Various techniques and algorithms have been developed to carry out the testing process. This paper deals with utility of the nature based algorithms namely Genetic Algorithm, Ant Colony Optimization algorithm and Artificial Bee Colony algorithm i...

This paper introduces an adaptive control method of strong mutation rate and probability for queen-bee genetic algorithms. Although the queen-bee genetic algorithms have shown good performances, it had a critical problem that the strong mutation rate and probability should be selected by a trial and error method empirically. In order to solve this problem, we employed the measure of convergence...

Phylogenies ; The evolutionary histories of groups of species are one of the most widely used tools throughout the life sciences, as well as objects of research with in systematic, evolutionary biology. In every phylogenetic analysis reconstruction produces trees. These trees represent the evolutionary histories of many groups of organisms, bacteria due to horizontal gene transfer and plants du...

Artificial bee colony (ABC) is a relatively new swarm intelligence based metaheuristic. It was successfully applied to various, mostly continuous, optimization problems. For all such heuristically guided search algorithms balance between exploitation and exploration is the determining factor for success. It is generally considered that in the ABC algorithm exploitation is performed by employed ...

Artificial bee colony (ABC) algorithm is an optimization algorithm based on a particular intelligent behaviour of honeybee swarms. This work compares the performance of ABC algorithm with that of differential evolution (DE), particle swarm optimization (PSO) and evolutionary algorithm (EA) for multi-dimensional numeric problems. The simulation results show that the performance of ABC algorithm ...

Background: Due to its nutrient content, a variety of spoilage microorganisms can grow in bee pollen, especially when handling practices are not appropriate. So, this survey was designed to assess the physicochemical and microbiological properties of bee pollen collected from Bulgaria. Methods: In June 2014, 13 fresh and 19 dried bee pollen samples were collected from Bulgaria. Water activity ...

The potency of various bee antigens including bee venom, several whole bee body extracts and fractions of bee venom was studied using the RAST inhibition method. As compared to whole bee body extract, bee venom was a much more potent inhibitor of both bee venom and whole body RAST, suggesting that venom has a greater capacity to bind specific bee IgE antibodies. Whole body extracts also varied ...