Word sense disambiguation (WSD) is a problem in the field of computational linguistics given as finding the intended sense of a word (or a set of words) when it is activated within a certain context. WSD was recently addressed as a combinatorial optimization problem in which the goal is to find a sequence of senses that maximize the semantic relatedness among the target words. In this article, ...

Scheduling tasks on computational grids is known as NPcomplete problem. Scheduling tasks in Grid computing, means assigning tasks to resources such that the time termination and average waiting time criteria and the number of required machines are optimized. Based on heuristic or meta-heuristic search have been proposed to obtain optimal solutions. The presented method tries to optimize all of ...

Back-propagation algorithm is one of the most widely used and popular techniques to optimize the feed forward neural network training. Nature inspired meta-heuristic algorithms also provide derivative-free solution to optimize complex problem. Artificial bee colony algorithm is a nature inspired meta-heuristic algorithm, mimicking the foraging or food source searching behaviour of bees in a bee...

Artificial bee colony (ABC) algorithm, inspired by the intelligent foraging behavior of honey bees, was proposed by Karaboga. It has been shown to be superior to some conventional intelligent algorithms such as genetic algorithm (GA), artificial colony optimization (ACO), and particle swarm optimization (PSO). However, the ABC still has some limitations. For example, ABC can easily get trapped ...

Software testing plays a vital role during the software development process, as it ensures quality deployment. Success of depends on design effective test cases. To achieve optimization generated cases, proposed approach combines both global and local searches by means intelligent agents which exhibit behaviour employed bees, onlooker scout bees in qABC algorithm. The algorithm has key improvem...

Recent developments of new families of pesticides and growing awareness of the importance of wild pollinators for crop pollination have stimulated interest in potential effects of novel pesticides on wild bees. Yet pesticide toxicity studies on wild bees remain rare, and few studies have included long-term monitoring of bumble bee colonies or testing of foraging ability after pesticide exposure...

Artificial bee colony (ABC) algorithm is a swarm intelligence optimization algorithm inspired by the intelligent behavior of honey bees when searching for food sources. The various versions of the ABC algorithm have been widely used to solve continuous and discrete optimization problems in different fields. In this paper a new binary version of the ABC algorithm inspired by quantum computing, c...

This paper systematically presents the Swarm Intelligence (SI) methods for optimization of multiple and many objective problems. The fundamental difference of Multiple andMany Objective Optimization problems have been studied very rigorously. The three forefront swarm intelligence methods, i.e., Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Artificial Bee Colony Optimiza...

Swarm intelligence is a research branch that models the population of interacting agents or swarms that are able to self-organize. An ant colony, a flock of birds or an immune system is a typical example of a swarm system. Bees’ swarming around their hive is another example of swarm intelligence. Artificial Bee Colony (ABC) Algorithm is an optimization algorithm based on the intelligent behavio...

Travelling salesman problem (TSP) is one the problems of NP-complete family, which means finding shortest complete close tour in graph. This study seeks to solve this using Artificial Bee Colony (ABC) Algorithm along with proposed Discrete Nearest Neighborhood (DNNA). DNNA finds path among points by starting from an arbitrary point. In next steps links will be a guide make tour. other words par...