The traveling salesman problem (TSP) is the problem of finding the shortest tour through all the nodes that a salesman has to visit. The TSP is probably the most famous and extensively studied problem in the field of combinatorial optimization. Because this problem is an NP-hard problem, practical large-scale instances cannot be solved by exact algorithms within acceptable computational times. ...

Assembly line balancing is significant for efficient and cost effective production of the products and is therefore gaining popularity in recent years. However, several uncertain events in assembly lines might causes variation in the task time and due to these variations there always remains a possibility that completion time of tasks might exceed the predefined cycle time. To hedge against thi...

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 ...

The minimum cross entropy thresholding (MCET) has been widely applied in image processing. In this paper, a new multilevel MCET algorithm based on the artificial bee colony (ABC) algorithm is proposed. The proposed thresholding algorithm is called ABC-based MCET algorithm. Four different methods including the exhaustive search, the honey bee mating optimization (HBMO), the particle swarm optimi...

This paper introduces a comparison of training algorithms of radial basis function (RBF) neural networks for classification purposes. RBF networks provide effective solutions in many science and engineering fields. They are especially popular in the pattern classification and signal processing areas. Several algorithms have been proposed for training RBF networks. The Artificial Bee Colony (ABC...

We propose an efficient parallel bundle adjustment (BA) algorithm to refine 3D reconstruction of the large-scale structure from motion (SfM) problem, which uses image collections from Internet. Different from the latest BA techniques that improve efficiency by optimizing the reprojection error function with Conjugate Gradient (CG) methods, we employ the parameter vector partition strategy. More...

permanent magnet synchronous generators (pmsgs) are novel generators which can be used in high-performance wind farms. high efficiency and flexibility in producing electricity from variable rotation make them good candidate for wind power applications. furthermore, because these kinds of generators have no excitation winding, there is no copper loss on rotor; hence, they can operate at high pow...

This paper empirically evaluates four meta-heuristic search techniques namely particle swarm optimization, artificial bee colony algorithm, Genetic Algorithm and Big Bang Big Crunch Algorithm for automatic test data generation for procedure oriented programs using structural symbolic testing method. Test data is generated for each feasible path of the programs. Experiments on ten benchmark prog...

The Artificial Bee Colony (ABC) algorithm is one of most popular stochastic, swarm based algorithm proposed by Karaboga in 2005 inspired from the foraging behaviour of honey bees. ABC has been applied to solve several problems in various fields and also many researchers have attempted to improve ABC’s performance by making some modifications. This paper proposes a new variant of ABC algorithm b...

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...