Job Scheduling plays an important role for efficient utilization of grid resources available across different domains and geographical zones. Scheduling of jobs is challenging and NPcomplete. Evolutionary / Swarm Intelligence algorithms have been extensively used to address the NP problem in grid scheduling. Artificial Bee Colony (ABC) has been proposed for optimization problems based on foragi...

With more and more various systems in nature and society are proved to be modeled as complex networks, community detection in complex networks as a fundamental problem becomes a hot research topic in a large scale of subjects. Artificial Bee Colony Algorithm (ABC) has high efficiency and does not require any prior knowledge about the number or the original division of the communities. So it is ...

This paper presents a new approach for solving the Combined Heat and Economic Dispatch (CHPED) problem using an artificial bee colony algorithm (ABC). Artificial Bee Colony algorithm (ABC) is inspired by the foraging behavior of honey bee swarm, is a biological inspired optimization. It shows more effective than the other optimization algorithms. The performance of the proposed algorithm ABC is...

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 ...

The idea behind this work is to solve the Shortest Common Supersequence by using Artificial Bee Colony (ABC) Algorithm. This algorithm is considered as one of the newest nature-inspired swarm-based optimization algorithms and has a promising performance [6]. Shortest Common Supersequence is a classical problem in the field of strings and it is classified as NP-Hard problem [12]. Many algorithms...

Determination of optimum location for drilling a new well not only requires engineering judgments but also consumes excessive computational time. Additionally, availability of many physical constraints such as the well length, trajectory, and completion type and the numerous affecting parameters including, well type, well numbers, well-control variables prompt that the optimization approaches b...

Artificial bee colony (ABC) algorithm, one of the swarm intelligence algorithms, has been proposed for continuous optimization, inspired intelligent behaviors of real honey bee colony. For the optimization problems having binary structured solution space, the basic ABC algorithm should be modified because its basic version is proposed for solving continuous optimization problems. In this study,...

The identification of values of solar cell parameters is of great interest for evaluating solar cell performances. The algorithm of an artificial bee colony was used to extract model parameters of solar cells from current-voltage characteristics. Firstly, the best-so-for mechanism was introduced to the original artificial bee colony. Then, a method was proposed to identify parameters for a sing...

 Numerous problems in engineering and science can be converted into optimization problems. Artificial bee colony (ABC) algorithm is a newly developed stochastic optimization algorithm and has been widely used in many areas. However, due to the stochastic characteristics of its solution search equation, the traditional ABC algorithm often suffers from poor exploitation. Aiming at this weakness o...