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The Bees Algorithm - Modelling Foraging Behav...
The Bees Algorithm - Modelling Foraging Behaviour to Solve Continuous Optimisation Problems
Main information
By:
Marco Castellani
(
CENTRIA
)
Date:
Wednesday, 22nd of April 2009, 14h00
Location:
FCT/UNL, Seminar Room (Ed. II)
Abstract
The Bees Algorithm models the foraging behaviour of honey bees in order to solve complex optimisation problems. The algorithm performs a kind of exploitative neighbourhood search combined with random explorative search. This talk describes the Bees Algorithm, and how it relates to other swarm intelligence techniques. The effectiveness of the Bees Algorithm is compared to that of three state-of-the-art biologically inspired search methods. The four algorithms were tested on a range of well known benchmark function optimisation problems of different degrees of complexity. The experimental results proved the reliability of the bees foraging metaphor. The experimental tests helped also to shed further light on the search mechanisms of the Bees Algorithm and the three control methods, and to highlight their differences, strengths, and weaknesses.
Short-bio
Marco Castellani obtained his Ph.D. degree in 2000 from University of Wales, Cardiff with a thesis on intelligent control of manufacturing of fibre optic components. Between 2001 and 2002, he worked for a private company in Germany on machine learning applications to natural language processing. Between 2002 and 2005, he was at New University of Lisbon, where his research included machine learning, machine vision, remote sensing and pattern recognition. Since December 2008 he is Research Fellow at the Manufacturing Engineering Centre of Cardiff University. His current research interests include machine learning, swarm intelligence, machine vision, and industrial quality control.
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