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.
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.
Impact and interest:
Citation counts are sourced monthly from and citation databases.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
|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 13:55|
Repository Staff Only: item control page