Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/63990
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Type: Conference paper
Title: Comparison of cooperative and classical evolutionary algorithms for global supply chain optimisation
Author: Ibrahimov, M.
Wagner, N.
Mohais, A.
Schellenberg, S.
Michalewicz, Z.
Citation: Proceedings of the IEEE Congress on Evolutionary Computation, part of the 2010 IEEE World Congress on Computational Intelligence, held in Barcelona, Spain 18-23 July 2010: pp.1-8
Publisher: IEEE
Publisher Place: USA
Issue Date: 2010
Series/Report no.: IEEE Congress on Evolutionary Computation
ISBN: 9781424481262
Conference Name: IEEE World Congress on Computational Intelligence (2010 : Barcelona, Spain)
Statement of
Responsibility: 
Maksud Ibrahimov, Neal Wagner, Arvind Mohais, Sven Schellenberg and Zbigniew Michalewicz
Abstract: This paper discusses global optimisation from a business perspective in the context of the supply chain operations. A two-silo supply chain was built for experimentation and two approaches were used for global optimisation: a classical evolutionary approach and a cooperative coevolutionary approach. The latter approach produced higher quality solutions due to its use of communication between silos. Additionally, a second problem was presented involving an existing Australian multi-factory sheet steel business.
Rights: ©2010 IEEE
DOI: 10.1109/CEC.2010.5586150
Grant ID: http://purl.org/au-research/grants/arc/DP0985723
http://purl.org/au-research/grants/arc/DP0985723
Published version: http://dx.doi.org/10.1109/cec.2010.5586150
Appears in Collections:Aurora harvest 5
Computer Science publications

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