There is a trend in the scientific community to model and solve complex optimization process by employing natural metaphors. In this area, Artificial Bee Colony optimization (ABC) tries to model natural behaviour of real honeybees in food foraging. ABC algorithm is an optimization algorithm based on the intelligent behaviour of honey bee swarm. In this work, ABC is used for solving multivariabl...

An important problem in nonlinear science is the unknown parameters estimation in Loranz chaotic system. Clearly, the parameter estimation for chaotic systems is a multidimensional continuous optimization problem, where the optimization goal is to minimize mean squared errors (MSEs) between real and estimated responses for a number of given samples. The Bees algorithm (BA) is a new member of me...

Many real-world search and optimization problems involve inequality and/or equality constraints and are thus posed as constrained optimization problems. In trying to solve constrained optimization problems using classical optimization methods, this paper presents a Multi-Objective Bees Algorithm (MOBA) for solving the multi-objective optimal of mechanical engineering problems design. In the pre...

Artificial bee colony (ABC) algorithm, inspired by the intelligent foraging behavior of honey bees, was proposed by Karaboga. It has been shown to be superior to some conventional intelligent algorithms such as genetic algorithm (GA), artificial colony optimization (ACO), and particle swarm optimization (PSO). However, the ABC still has some limitations. For example, ABC can easily get trapped ...

Multi-join query optimization is an important technique for designing and implementing database management system. It is a crucial factor that affects the capability of database. This paper proposes a Bees algorithm that simulates the foraging behavior of honey bee swarm to solve Multi-join query optimization problem. The performance of the Bees algorithm and Ant Colony Optimization algorithm a...

Multi-join query optimization is an important technique for designing and implementing database management system. It is a crucial factor that affects the capability of database. This paper proposes a Bees algorithm that simulates the foraging behavior of honey bee swarm to solve Multi-join query optimization problem. The performance of the Bees algorithm and Ant Colony Optimization algorithm a...

This article introduces two swarm intelligent algorithms, a group search optimizer (GSO) and an artificial fish swarm algorithm (AFSA). A single intelligent algorithm always has both merits in its specific formulation and deficiencies due to its inherent limitations. Therefore, we propose a mixture of these algorithms to create a new hybrid optimization algorithm known as the group search-artif...

This paper introduces a variant of Artificial Bee Colony algorithm and compares its results with a number of swarm intelligence and population based optimization algorithms. The Artificial Bee Colony (ABC) is an optimization algorithm based on the intelligent food foraging behavior of honey bees. The proposed variant, Artificial Bee Colony Algorithm with Balanced Explorations and Exploitations ...

Software testing plays a vital role during the software development process, as it ensures quality deployment. Success of depends on design effective test cases. To achieve optimization generated cases, proposed approach combines both global and local searches by means intelligent agents which exhibit behaviour employed bees, onlooker scout bees in qABC algorithm. The algorithm has key improvem...