In this paper, the bee colony algorithm is used for optimizing features which have been extracted from UAV’s digital camera by SURF algorithm. To do that, the local map is stored in UAV memory before flight. During flight, images will be captured by a digital camera and the features in successive image will be extracted using SURF algorithm because SURF algorithm is considered highly insensitiv...

Kernel fuzzy C-mean clustering (KFCM) algorithm is effective for high-dimensional data, but this algorithm has some defects of sensitivity to initialization and local optima. Artificial Bee Colony (ABC) algorithm is based on intelligent behaviors of honey bee swarm. It has the properties of strong global optimization and fast convergence speed. A KFCM algorithm based on improved ABC is proposed...

Proper management of locations of the mobile devices is of great importance in this era of wireless communication networks, as the use of the mobile devices has grown exponentially. The registration area planning (RAP) problem aims to group the wireless network cells into contiguous areas called registration areas in order to minimize the cost of managing the location of mobile devices. Since t...

Routing and Wavelength Assignment (RWA) problem in all-optical networks assumes determining the routes and wavelengths to be used to create the lightpaths for connection requests. The RWA problem belongs to a class of difficult combinatorial optimization problems. We propose the Bee Colony Optimization (BCO) heuristic algorithm tailored for the RWA problem (BCO–RWA) in all-optical networks with...

Artificial Bee colony is one of the most efficient optimizing technique introduced so far. Artificial Bee Colony simulates the brilliant behavior honey bee swarm. Considering the environmental impacts that grow from the emission produced by the conventional fuel power plants, the economic dispatch that minimizes only the total fuel cost can no longer be considered as single objective function. ...

In this paper, we propose a novel artificial bee colony(ABC) algorithm for the multidimensional knapsack problems, which introduces the attraction pheromone and presents a transition strategy based on the attraction pheromone. In our algorithm, the scout generates a food source according to the transition strategy and replaces the abandoned food source by comparison with the corresponding elite...

In recent years large number of algorithms based on the swarm intelligence has been proposed by various researchers. The Artificial Bee Colony (ABC) algorithm is one of most popular stochastic, swarm based algorithm proposed by Karaboga in 2005 inspired from the foraging behavior of honey bees. In short span of time, ABC algorithm has gain wide popularity among researchers due to its simplicity...

Artificial Bee Colony (ABC) is one of the most recent nature inspired (NIA) algorithms based on swarming metaphor. Proposed by Karaboga in 2005, ABC has proven to be a robust and efficient algorithm for solving global optimization problems over continuous space. However, it has been observed that the structure of ABC is such that it supports exploration more in comparison to exploitation. In or...

http://dx.doi.org/10.1016/j.ins.2014.04.013 0020-0255/ 2014 Elsevier Inc. All rights reserved. ⇑ Corresponding author. Tel.: +86 0791 88126661; fax: +86 0791 88126660. E-mail addresses: [email protected] (H. Wang), [email protected] (Z. Wu), [email protected] (S. Rahn [email protected] (H. Sun), [email protected] (Y. Liu), [email protected] (J.-s. Pan). Hui Wang a,⇑, Zhijian ...