Artificial Bee Colony (ABC) algorithm was firstly proposed for unconstrained optimization problems on where that ABC algorithm showed superior performance. This paper describes a modified ABC algorithm for constrained optimization problems and compares the performance of the modified ABC algorithm against those of state-of-the-art algorithms for a set of constrained test problems. For constrain...

A rtificial bee Colony algorithm (ABC) is a population based heuristic search technique used for optimization problems. ABC is a very effective optimization technique for continuous optimization problem. Crossover operators have a better exploration property so crossover operators are added to the ABC. This paper presents ABC with different types of real coded crossover operator and its applica...

The Artificial Bee Colony (ABC) algorithm is a population based meta-heuristic algorithm proposed by Karaboga in 2005 inspired by the intelligent foraging behaviour of honey bees. ABC as a powerful technique is easy to implement, has fewer control parameters, and could easily be integrated with other meta-heuristic algorithms due to which it continues to attract the interest of researchers from...

Nature inspired metaheuristics proved to be very successful when applied to hard optimization problems, combinatorial as well as global. For all these algorithms, with very different basic ideas, parameters and implementation details, the common problem that ultimately determines the successfulness of a particular algorithm is balance between exploitation and exploration. Exploitation refers to...

In the paper, hybrid technique for solving optimal power flow problems that occur in power systems. The proposed hybrid technique is the combination of artificial bee colony (ABC) algorithm and artificial intelligence (AI) technique. The purpose of the ABC algorithm is used to optimize the optimal operating range of generation limits. So, the fuel cost and the emission of the power generation s...

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...

A major problem with the Artificial Bee Colony (ABC) algorithm is its premature convergence to the locally optimal points of the search space, which often originates from the lack of explorative search capability of its mutation operator. This paper introduces ABC with Adaptive Mutation Rate (ABC-AMR), a novel algorithm that modifies the basic mutation operation of the original ABC algorithm in...

So many techniques are used in the software testing environment and in this paper we survey the ABC algorithmic approach and its advantages over the GA (Genetic Algorithms). Artificial bee colony (ABC) algorithm is one of the most recently introduced swarm–based algorithms. These optimization approaches helps in memorization and also support the global optima. This algorithm is based on colony ...

In this paper we investigate iterative logic synthesis processes. A well known academic logic synthesis tool ABC incorporates many synthesis algorithms and scripts which may be run iteratively to possibly improve the result. When iterating the synthesis process, the whole network is considered. We propose an alternative approach to iterative synthesis – only properly selected parts of the circu...