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Fast optimization by Demon Algorithms

Wood, Ian A. & Downs, Tom (1998) Fast optimization by Demon Algorithms. In Downs, Tom, Frean, Marcus, & Gallagher, Marcus (Eds.) Australian Conference on Neural Networks 1998, February 11-13, University of Queensland, Brisbane, QLD, Australia.

Abstract

We introduce four new general optimization algorithms based on the `demon' algorithm from statistical physics and the simulated annealing (SA) optimization method. These algorithms use a computationally simpler acceptance function, but can use any SA annealing schedule or move generation function. Computation per trial is significantly reduced. The algorithms are tested on traveling salesman problems including Grotschel's 442-city problem and the results are comparable to those produced using SA. Applications to the Boltzmann machine are considered.

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ID Code: 5725
Item Type: Conference Paper
Keywords: demon algorithm, optimization, traveling salesman problem
Subjects: Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 1998 (The authors)
Deposited On: 04 Dec 2006
Last Modified: 10 Aug 2011 23:55

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