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Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/10464

Title: A hybrid intelligent algorithm for solving the bilevel programming models
Authors: Shamsul Bahar, Yaakob, Prof. Madya
Watada, Junzo
???metadata.dc.contributor.url???: shamshul@unimap.edu.my
Keywords: Bilevel programming model;Neural network;Boltzmann machine;Hopfield network;Meta-controlled Boltzmann machine
Issue Date: 2010
Publisher: Springer-Verlag
Citation: Lecture Notes in Computer Science, vol. 6277(2), 2010, pages 485-494
Series/Report no.: 14th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (KES) 2010
Abstract: In this paper, genetic algorithm (GA) and neural network (NN) are integrated to produce a hybrid intelligent algorithm for solving the bilevel programming models. GA is used to select a set of potential combination from the entire generated combination. Then a meta-controlled Boltzmann machine which is formulated by comprising a Hopfield network and a Boltzmann machine (BM) is used to effectively and efficiently determine the optimal solution. The proposed method is used to solve the examples of bilevel programming for two- level investment in a new facility. The upper layer will decide the optimal company investment. The lower layer is used to decide the optimal department investment. Typical application examples are provided to illustrate the effectiveness and practicability of the hybrid intelligent algorithm.
Description: Link to publisher's homepage at http://www.springerlink.com/
URI: http://www.springerlink.com/content/q7r67gkk3j622864/fulltext.pdf
http://hdl.handle.net/123456789/10464
ISBN: 978-3-6421-5389-1
3642153895
ISSN: 0302-9743
Appears in Collections:Conference Papers

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