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
Annals of Operations Research – Springer Journals
Published: Jun 4, 2018
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