Hybrid Differential Artificial Bee Colony Algorithm
Artificial Bee Colony Algorithm (ABCA) is a new population-based meta-heuristic approach inspired by the foraging behaviour of bees. This article describes an application of a novel Hybrid Differential Artificial Bee Colony Algorithm (HDABCA), which combines Differential Evolution strategy
with Artificial Bee Colony algorithm. We illustrate the proposed method using several test functions and also compared with classical differential evolution algorithm and artificial bee colony algorithm. Simulation results illustrate that the proposed method is very efficient.
Keywords: ARTIFICIAL BEE COLONY; DIFFERENTIAL EVOLUTION; OPTIMIZATION MODELS
Document Type: Research Article
Publication date: 01 February 2012
- Journal of Computational and Theoretical Nanoscience is an international peer-reviewed journal with a wide-ranging coverage, consolidates research activities in all aspects of computational and theoretical nanoscience into a single reference source. This journal offers scientists and engineers peer-reviewed research papers in all aspects of computational and theoretical nanoscience and nanotechnology in chemistry, physics, materials science, engineering and biology to publish original full papers and timely state-of-the-art reviews and short communications encompassing the fundamental and applied research.
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