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

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. Th...

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Published in:Annals of operations research Vol. 286; no. 1-2; pp. 583 - 615
Main Authors: Hinz, Juri, Tarnopolskaya, Tanya, Yee, Jeremy
Format: Journal Article
Language:English
Published: New York Springer US 01.03.2020
Springer
Springer Nature B.V
Subjects:
Algorithms
Business and Management
Combinatorics
Control methods
Data mining
Decision making
Diagnostic systems
Dynamic programming
Mathematical research
Mining industry
Operations research
Operations Research/Decision Theory
Optimal control
Optimization
S.i.: Claio 2016
Stochastic processes
Studies
Theory of Computation
Australia
Optimal switching
Approximate dynamic programming
Markov decision process
Duality
Natural resource extraction
Real option
ISSN:0254-5330, 1572-9338
Online Access:Get full text
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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.
AbstractList 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.
Audience Academic
Author Hinz, Juri
Tarnopolskaya, Tanya
Yee, Jeremy
Author_xml – sequence: 1
  givenname: Juri
  surname: Hinz
  fullname: Hinz, Juri
  email: Juri.Hinz@uts.edu.au
  organization: University of Technology Sydney
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  givenname: Tanya
  surname: Tarnopolskaya
  fullname: Tarnopolskaya, Tanya
  organization: CSIRO
– sequence: 3
  givenname: Jeremy
  surname: Yee
  fullname: Yee, Jeremy
  organization: University of Technology Sydney, CSIRO
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crossref_primary_10_3390_jrfm14060235
crossref_primary_10_1111_poms_13250
crossref_primary_10_1007_s10479_020_03569_w
crossref_primary_10_1155_2021_4848036
crossref_primary_10_1007_s10479_022_05074_8
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Copyright Springer Science+Business Media, LLC, part of Springer Nature 2018
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Approximate dynamic programming
Markov decision process
Duality
Natural resource extraction
Real option
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SubjectTerms Algorithms
Business and Management
Combinatorics
Control methods
Data mining
Decision making
Diagnostic systems
Dynamic programming
Mathematical research
Mining industry
Operations research
Operations Research/Decision Theory
Optimal control
Optimization
S.i.: Claio 2016
Stochastic processes
Studies
Theory of Computation
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Title Efficient algorithms of pathwise dynamic programming for decision optimization in mining operations
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