A Monte Carlo knowledge gradient method for learning abatement potential of emissions reduction technologies

Ilya O. Ryzhov, Warren Buckler Powell

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

8 Scopus citations

Abstract

Suppose that we have a set of emissions reduction technologies whose greenhouse gas abatement potential is unknown, and we wish to find an optimal portfolio (subset) of these technologies. Due to the interaction between technologies, the effectiveness of a portfolio can only be observed through expensive field implementations. We view this problem as an online optimal learning problem with correlated prior beliefs, where the performance of a portfolio of technologies in one project is used to guide choices for future projects. Given the large number of potential portfolios, we propose a learning policy which uses Monte Carlo sampling to narrow down the choice set to a relatively small number of promising portfolios, and then applies a one-period look-ahead approach using knowledge gradients to choose among this reduced set. We present experimental evidence that this policy is competitive against other online learning policies that consider the entire choice set.

Original languageEnglish (US)
Title of host publicationProceedings of the 2009 Winter Simulation Conference, WSC 2009
Pages1492-1502
Number of pages11
DOIs
StatePublished - Dec 1 2009
Event2009 Winter Simulation Conference, WSC 2009 - Austin, TX, United States
Duration: Dec 13 2009Dec 16 2009

Publication series

NameProceedings - Winter Simulation Conference
ISSN (Print)0891-7736

Other

Other2009 Winter Simulation Conference, WSC 2009
CountryUnited States
CityAustin, TX
Period12/13/0912/16/09

All Science Journal Classification (ASJC) codes

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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    Ryzhov, I. O., & Powell, W. B. (2009). A Monte Carlo knowledge gradient method for learning abatement potential of emissions reduction technologies. In Proceedings of the 2009 Winter Simulation Conference, WSC 2009 (pp. 1492-1502). [5429301] (Proceedings - Winter Simulation Conference). https://doi.org/10.1109/WSC.2009.5429301