Numerous problems in engineering and science can be converted into optimization problems. Artificial bee colony (ABC) algorithm is a newly developed stochastic optimization algorithm and has been widely used in many areas. However, due to the stochastic characteristics of its solution search equation, the traditional ABC algorithm often suffers from poor exploitation. Aiming at this weakness o...

The idea behind this work is to solve the Shortest Common Supersequence by using Artificial Bee Colony (ABC) Algorithm. This algorithm is considered as one of the newest nature-inspired swarm-based optimization algorithms and has a promising performance [6]. Shortest Common Supersequence is a classical problem in the field of strings and it is classified as NP-Hard problem [12]. Many algorithms...

Artificial Bee Colony (ABC) algorithm simulates the foraging behavior of honey bee colonies. ABC is an optimization technique, which is used in finding the best solution from all feasible solutions. However, there is still an insufficiency in ABC regarding improvement in exploitation and convergence speed. In order to improve the performance of ABC we embedded PSO into ABC. As PSO has memory, k...

Article Bee Colony (ABC) is one of the most recently introduced algorithms based on the intelligent foraging behavior of a honey bee swarm. This paper proposes a new variant of the ABC algorithm based on Von Neumann topology structure, namely Von Neumann Neighborhood Article Bee Colony (VABC). VABC significantly improves the original ABC in solving complex optimization problems. Clustering is a...

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. ...

Artificial Bee Colony (ABC) Algorithm is an optimization algorithm used to find out the global optima. In ABC, each bee stores the information of feasible solution or candidate solution and stochastically modifies this over time, based on the information provided by neighboring bees, it speculative modifies over time and based on the best solution found by the bee itself. . In this proposed wor...

In this paper, a compact Articial Bee Colony optimization method (cABC) for applying to the topology optimization of wireless sensor networks (WSNs) is presented. The purpose of compact algorithms is to address to the computational requirements in the limited resources of hardware devices such as memory size or low price. A probabilistic representation random of the collection behavior of socia...

Most reservoirs offer a mean of managing and regulating the downstream water flow and demands over time and space. It is a challenging task for the reservoir operator to evaluate the trade-off during drought and heavy rainfall season. This study proposes a review on the application of different computational intelligent models, especially the Artificial Bee Colony (ABC) approach in reservoir in...

This research explains airplane model with two vertical vibrations for airframe and landing gear system. The purpose of this work is to advance vibrational model for study of adjustable vibration absorber and to plan Proportional-Integration-Derivative approach for adapting semi active control force. The coefficients of this method are modified as stated by Bee multiobjective optimization using...

One of the most well-known binary (discrete) versions of the artificial bee colony algorithm is the similarity measure based discrete artificial bee colony, which was first proposed to deal with the uncapacited facility location (UFLP) problem. The discrete artificial bee colony simply depends on measuring the similarity between the binary vectors through Jaccard coefficient. Although it is acc...