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...

Artificial Bee Colony (ABC) algorithm is a relatively new swarm intelligence algorithm which has shown a competitive performance with respect to other population-based algorithms. However, there are still some insufficiencies in ABC algorithm such as slow convergence and easily trapped in local optima. These drawbacks can be even more challenging when constraints are also involved. To address t...

In data mining, Association rule mining is one of the popular and simple method to find the frequent item sets from a large dataset. While generating frequent item sets from a large dataset using association rule mining, computer takes too much time. This can be improved by using artificial bee colony algorithm (ABC). The Artificial bee colony algorithm is an optimization algorithm based on the...

In this work, performance of the Artificial Bee Colony Algorithm which is a recently proposed algorithm, has been tested on fuzzy clustering. We applied the Artificial Bee Colony (ABC) Algorithm fuzzy clustering to classify different data sets; Cancer, Diabetes and Heart from UCI database, a collection of classification benchmark problems. The results indicate that the performance of Artificial...

optimal sitting and sizing of shunt capacitor banks at the distribution networks for the purpose of power quality improvement is drawn much attention of electric power utilities in the last decades. determining the optimal number, location and sizing of capacitor using bee colony optimization algorithm (bco) is being presented in this paper. the bco algorithm is a new population based meta-heur...

Software test suite optimization is one of the most important issue in software testing as testing consumes a lot of time in executing redundant test cases. In this paper, we have proposed and implemented a new approach for test suite optimization, namely, Mutated Artificial Bee Colony. Artificial Bee colony algorithm combines local search carried out by employed and onlooker bees with global s...

Environmental pollution and emissions, along with the increasing production and distribution of goods, have placed the future of humanity at stake. Today, measures such as the extensive reduction in emissions, especially of CO2 and CO, have been emphasized by most researchers as a solution to the problem of environmental protection. This paper sought to explore production routing pro...

although lot streaming scheduling is an active research field, lot streaming flexible flow lines problems have received far less attention than classical flow shops. this paper deals with scheduling jobs in lot streaming flexible flow line problems. the paper mathematically formulates the problem by a mixed integer linear programming model. this model solves small instances to optimality. moreo...

Artificial Bee Colony (ABC) algorithm is a Nature Inspired Algorithm (NIA) which based on intelligent food foraging behaviour of honey bee swarm. This paper introduces a local search strategy that enhances exploration competence of ABC and avoids the problem of stagnation. The proposed strategy introduces two new local search phases in original ABC. One just after onlooker bee phase and one aft...

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 technique based on the intelligent foraging behavior of honey bees. We present a 2-level metaheuristic approach where an Artificial Bee Colony Algorithm acts as a low-level metaheuristic and its paremeters are se...