Approximate dynamic programming for high dimensional resource allocation problems

Warren Buckler Powell, Abraham George, Belgacem Bouzaiene-Ayari, Hugo P. Simao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

There are a wide array of discrete resource allocation problems (buffers in manufacturing, complex equipment in electric power, aircraft and locomotives in transportation) which need to be solved over time, under uncertainty. These can be formulated as dynamic programs, but typically exhibit high dimensional state, action and outcome variables (the three curses of dimensionality). For example, we have worked on problems where the dimensionality of these variables is in the ten thousand to one million range. We describe an approximation methodology for this problem class, and summarize the problem classes where the approach seems to be working well, and research challenges that we continue to face.

Original languageEnglish (US)
Title of host publicationProceedings of the International Joint Conference on Neural Networks, IJCNN 2005
Pages2989-2994
Number of pages6
DOIs
StatePublished - Dec 1 2005
EventInternational Joint Conference on Neural Networks, IJCNN 2005 - Montreal, QC, Canada
Duration: Jul 31 2005Aug 4 2005

Publication series

NameProceedings of the International Joint Conference on Neural Networks
Volume5

Other

OtherInternational Joint Conference on Neural Networks, IJCNN 2005
CountryCanada
CityMontreal, QC
Period7/31/058/4/05

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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