In this paper we present a modification of artificial bee colony (ABC) algorithm for constrained optimization problems. In nature more than one onlooker bee goes to a promising food source reported by employed bee. Our proposed modification forms a mutant solution in onlooker phase using three onlookers. This approach obtains better results than the original artificial bee colony algorithm. Our...

In this paper, a new discrete artificial bee colony algorithm is used to solve the symmetric traveling salesman problem (TSP). The concept of Swap Operator has been introduced to the original artificial bee colony (ABC) algorithm which can help the bees to generate a better candidate tour by greedy selection. By taken six typical TSP instances as examples, the proposed algorithm is compared wit...

Grid computing is a new computing model; it’s performing bulk operations among the connected network. Since it is possible to run multiple applications simultaneously may require multiple resources but often do not have the resources that time scheduling system is essential for allocating resources. Scheduling algorithms must be designed for Maximize utilization of the resources and minimize th...

The artificial bee colony (ABC) algorithm is an evolutionary optimization based on swarm intelligence and inspired by the honey bees’ food search behavior. Since ABC has been developed to achieve optimal solutions searching in continuous space, modification required apply it binary problems. In this study, we modify solve problems name improved (IbinABC). proposed method consists of update mech...

Artificial bee colony algorithm simulating the intelligent foraging behavior of honey bee swarms is one of the most popular swarm based optimization algorithms. It has been introduced in 2005 and applied in several fields to solve different problems up to date. In this paper, an artificial bee colony algorithm, called as Artificial Bee Colony Programming (ABCP), is described for the first time ...

The set covering problem is a formal model for many practical optimization problems. In the set covering problem the goal is to choose a subset of the columns of minimal cost that covers every row. Here, we present a novel application of the artificial bee colony algorithm to solve the non-unicost set covering problem. The artificial bee colony algorithm is a recent swarm metaheuristic techniqu...

Many different earning algorithms used for getting high performance in mathematics and statistical tasks. Recently, an Artificial Bee Colony (ABC) developed by Karaboga is a nature inspired algorithm, which has been shown excellent performance with some standard algorithms. The hybridization and improvement strategy made ABC more attractive to researchers. The two famous improved algorithms are...

The Weighted Set Covering Problem is a formal model for many practical optimization problems. In this problem the goal is to choose a subset of columns of minimal cost covering every row. Here, we present a novel application of the Artificial Bee Colony algorithm to solve the Weighted Set Covering Problem. The Artificial Bee Colony algorithm is a recent Swarm Metaheuristic technique based on th...

The job shop scheduling problem (JSSP) is an NP-hard problem of wide engineering and theoretical background. In this paper, a discrete artificial bee colony based memetic algorithm, named DABC, is proposed for solving JSSP. Firstly, to make artificial bee colony (ABC) suitable for solving JSSP, we present a food source as a discrete job permutation and use the discrete operation to generate a n...