By integrating artificial bee colony and genetic algorithm, a novel hybrid swarm intelligent approach is proposed in this paper. The main idea of the approach is to obtain the parallel computation merit of GA and the speed and self-improvement merits of ABC by sharing information between GA population and bee colony. To exam the proposed method, it is applied to 4 benchmark functions for differ...

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...

This paper propose a new mixture method called Quantum Artificial Bee Colony (QABC) algorithm. QABC is based on some quantum computing concepts, such as qubits and superposition of states. In QABC these quantum concepts are applied on Artificial Bee Colony (ABC) algorithm. ABC is one of the recent algorithms in optimization area that has earned good popularity and some new works based on origin...

Nowadays computers are used to solve a variety and multitude of complex problems facing in every sphere of peoples’ life. However, many of the problems are intractable in nature exact algorithm might need centuries to manage with formidable challenges. In such cases heuristic or in a broader sense meta-heuristic algorithms that find an approximate solution but have acceptable time and space com...

Received Oct 14,2012 Revised Jan 05, 2013 Accepted March 02,2013 In practical cases, the fuel cost of generators can be represented as a quadratic function of real power generation and satisfied constraints for minimizing of fuel cost. Artificial bee colony (ABC) algorithm is used for the optimization of active power dispatch of generating units. The proposed method is able to determine, the ou...

Over the past few years, swarm intelligence based optimization techniques such as ant colony optimization and particle swarm optimization have received considerable attention from engineering researchers. These algorithms have been used in the solution of various structural optimization problems where the main goal is to minimize the weight of structures while satisfying all design requirements...

ABC (Artificial Bee Colony) algorithm is one of the most popular approaches that is used in optimization problems. ABC overcomes other well-known heuristic methods, such as GA, PSO and DE (Differential Evolution). In this paper, we propose a hybrid ABC-DE algorithm that combines properties of ABC and DE approaches. The results show that our proposed algorithm is better than both ABC and DE and ...

 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...

Data visualization is the process of transforming data, information, and knowledge into visual form, making use of humans’ natural visual capabilities which reveals relationships in data sets that are not evident from the raw data, by using mathematical techniques to reduce the number of dimensions in the data set while preserving the relevant inherent properties. In this paper, we formulated d...

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 ...