In this paper a hybrid model called Particle Swarm Artificial Bee Colony algorithm (PSABC) has been proposed. The PSABC algorithm is a combination of Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithm. PSABC has been used in this context to optimize the fitness value of a population in ABC algorithm using Particle Swarm Optimization. PSABC could be used to optimize the ...

This paper presents the comparison results on the performance of the Artificial Bee Colony (ABC) algorithm for constrained optimization problems. The ABC algorithm has been firstly proposed for unconstrained optimization problems and showed that it has superior performance on these kind of problems. In this paper, the ABC algorithm has been extended for solving constrained optimization problems...

We present a stochastic, swarm intelligence-based optimization algorithm for the prediction of global minima on potential energy surfaces of molecular cluster structures. Our optimization approach is a modification of the artificial bee colony (ABC) algorithm which is inspired by the foraging behavior of honey bees. We apply our modified ABC algorithm to the problem of global geometry optimizat...

Bee colony optimization (BCO) is one of the most recent algorithms in swarm intelligence that can be used in optimization problems this algorithm is based on the intelligent behavior of honey bees in foraging process. In this paper bee colony optimization is applied to solve the task scheduling problem which tasks have dependency with each other. Scheduling of tasks that represents by directed ...

In this paper, we present a new Artificial Bee Colony algorithm to solve the non-unicost Set Covering Problem. The Artificial Bee Colony algorithm is a recent metaheuristic technique based on the intelligent foraging behavior of honey bee swarm. Computational results show that Artificial Bee Colony algorithm is competitive in terms of solution quality with other metaheuristic approaches for the...

This paper presents a new Artificial Bee Colony (ABC) optimization algorithm to solve function optimization problems. The proposed approach is called OCABC, which introduces opposition-based learning concept and dynamic Cauchy mutation into the standard ABC algorithm. To verify the performance of OCABC, eight well-known benchmark function optimization problems are used in the experiments. Exper...

Artificial bee colony (ABC) algorithm invented recently by Karaboga is a biological-inspired optimization algorithm, which has been shown to be competitive with some conventional biological-inspired algorithms, such as genetic algorithm (GA), differential evolution (DE) and particle swarm optimization (PSO). However, there is still an insufficiency in ABC algorithm regarding its solution search...

Nowadays computers are used to solve a variety and multitude of complex problems facing in every sphere of peoples’ life. However, many of the problems are intractable in nature exact algorithm might need centuries to manage with formidable challenges. In such cases heuristic or in a broader sense meta-heuristic algorithms that find an approximate solution but have acceptable time and space com...