Efficient algorithms of pathwise dynamic programming for decision optimization in mining operations

Efficient algorithms of pathwise dynamic programming for decision optimization in mining operations Ann Oper Res https://doi.org/10.1007/s10479-018-2910-3 S.I.: CLAIO 2016 Efficient algorithms of pathwise dynamic programming for decision optimization in mining operations 1 2 1,2 Juri Hinz · Tanya Tarnopolskaya · Jeremy Yee © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract Complexity and uncertainty associated with commodity resource valuation and extraction requires stochastic control methods suitable for high dimensional states. Recent progress in duality and trajectory-wise techniques has introduced a variety of fresh ideas to this field with surprising results. This paper presents a concept which implements this promising development and illustrates it on a selection of traditional commodity extraction problems. We describe efficient algorithms for obtaining approximate solutions along with a diagnostic technique, which provides a quantitative measure for solution performance in terms of the distance between the approximate and the optimal control policy. All quantitative tools are efficiently implemented and are publicly available within a user friendly package in the statistical language R, which can help practitioners in a broad range of decision optimization problems. Keywords Approximate dynamic programming · Duality · Markov decision process · Natural resource extraction · Optimal switching · Real option 1 Introduction Extraction projects for commodities, their valuation and operational management can http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Operations Research Springer Journals

Efficient algorithms of pathwise dynamic programming for decision optimization in mining operations

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Business and Management; Operations Research/Decision Theory; Combinatorics; Theory of Computation
ISSN
0254-5330
eISSN
1572-9338
D.O.I.
10.1007/s10479-018-2910-3
Publisher site
See Article on Publisher Site

Abstract

Ann Oper Res https://doi.org/10.1007/s10479-018-2910-3 S.I.: CLAIO 2016 Efficient algorithms of pathwise dynamic programming for decision optimization in mining operations 1 2 1,2 Juri Hinz · Tanya Tarnopolskaya · Jeremy Yee © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract Complexity and uncertainty associated with commodity resource valuation and extraction requires stochastic control methods suitable for high dimensional states. Recent progress in duality and trajectory-wise techniques has introduced a variety of fresh ideas to this field with surprising results. This paper presents a concept which implements this promising development and illustrates it on a selection of traditional commodity extraction problems. We describe efficient algorithms for obtaining approximate solutions along with a diagnostic technique, which provides a quantitative measure for solution performance in terms of the distance between the approximate and the optimal control policy. All quantitative tools are efficiently implemented and are publicly available within a user friendly package in the statistical language R, which can help practitioners in a broad range of decision optimization problems. Keywords Approximate dynamic programming · Duality · Markov decision process · Natural resource extraction · Optimal switching · Real option 1 Introduction Extraction projects for commodities, their valuation and operational management can

Journal

Annals of Operations ResearchSpringer Journals

Published: Jun 4, 2018

References

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