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...

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...

In this paper, we propose a novel artificial bee colony(ABC) algorithm for the multidimensional knapsack problems, which introduces the attraction pheromone and presents a transition strategy based on the attraction pheromone. In our algorithm, the scout generates a food source according to the transition strategy and replaces the abandoned food source by comparison with the corresponding elite...

Artificial Bee Colony (ABC) algorithm is a relatively new swarm intelligence algorithm that has attracted great deal of attention from researchers in recent years with the advantage of less control parameters and strong global optimization ability. However, there is still an insufficiency in ABC regarding its solution search equation, which is good at exploration but poor at exploitation. This ...

This research work, proposes an ABC (Artificial Bee Colony Optimization) based framework, motivated by the intelligent behavior of honey bees to automate the test suite optimization process. Here, the bees are implemented as agents that perform the test suite optimization activities seamlessly. Since, the ABC system combines local search methods carried out by employed and onlooker bees with gl...

This paper suggests a dynamic multi-colony multi-objective artificial bee colony algorithm (DMCMOABC) by using the multi-deme model and a dynamic information exchange strategy. In the proposed algorithm, K colonies search independently most of the time and share information occasionally. In each colony, there are S bees containing equal number of employed bees and onlooker bees. For each food s...

Swarm intelligence systems are typically made up of a population of simple agents or boids interacting locally with one another and with their environment. Particle swarm, Ant colony, Bee colony are examples of swarm intelligence. In the field of computer science and operations research, Artificial Bee Colony Algorithm (ABC) is an optimization algorithm based on the intelligent foraging behavio...

Clustering is having the significance to generate effective data segments based on feature and dimension evaluation. In this work, an ABC improved Hierarchical clustering method is defined. The method has divided the clustering activities for different types of bees with their relative role assignment. The scout bee defined as the controller and the onlooker bees are defined as the cluster agen...

Artificial bee colony is a population-based search algorithm that mimics a natural behavior of real honey bees to find rich food sources to obtain maximum quantity of nectar and share the information of food sources with other bees in the hive. This paper concerns primarily about how to use artificial bee colony to solve examination timetabling problems which it is known as a NP-hard problem. I...