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Mine-to-client planning with Markov Decision Process

Mine-to-client planning with Markov Decision Process
Mine-to-client planning with Markov Decision Process
This works presents an innovative application of Markov Decision Process (MDP) to a medium-term mining logistics planning problem considering the mine-to-client supply chain. We implemented three distinct algorithms based on state-of-the-art approaches to solve large-scale problems, and compared their results. Furthermore, we combined all three variants in a single novel algorithm that attained fast convergence and may be an alternative to circumvent the curse of dimensionality underlying large scale problems.
Computational modeling, Dynamic Programming, MDP, Markov Decision Processes, Markov decision process, Markov processes, Mining Industry, Operational Research, Planning, Supply Chain, Supply chains, Uncertainty, distinct algorithms, innovative application, medium-term mining logistics planning problem, mine-to-client supply chain planning, mining industry, planning, supply chains
1123-1128
IEEE
Leite, J. M. Leal Gomes
e0517d87-f324-4924-abaf-ccf92ccf156b
Arruda, E. F.
8eb3bd83-e883-4bf3-bfbc-7887c5daa911
Bahiense, L.
48a5c2a4-d43b-4445-983f-e0637753074e
Marujo, L. G.
6179c7ff-0187-40b6-b04a-e2cff32580f5
Leite, J. M. Leal Gomes
e0517d87-f324-4924-abaf-ccf92ccf156b
Arruda, E. F.
8eb3bd83-e883-4bf3-bfbc-7887c5daa911
Bahiense, L.
48a5c2a4-d43b-4445-983f-e0637753074e
Marujo, L. G.
6179c7ff-0187-40b6-b04a-e2cff32580f5

Leite, J. M. Leal Gomes, Arruda, E. F., Bahiense, L. and Marujo, L. G. (2020) Mine-to-client planning with Markov Decision Process. In European Control Conference 2020, ECC 2020. IEEE. pp. 1123-1128 . (doi:10.23919/ECC51009.2020.9143651).

Record type: Conference or Workshop Item (Paper)

Abstract

This works presents an innovative application of Markov Decision Process (MDP) to a medium-term mining logistics planning problem considering the mine-to-client supply chain. We implemented three distinct algorithms based on state-of-the-art approaches to solve large-scale problems, and compared their results. Furthermore, we combined all three variants in a single novel algorithm that attained fast convergence and may be an alternative to circumvent the curse of dimensionality underlying large scale problems.

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More information

Published date: 1 May 2020
Keywords: Computational modeling, Dynamic Programming, MDP, Markov Decision Processes, Markov decision process, Markov processes, Mining Industry, Operational Research, Planning, Supply Chain, Supply chains, Uncertainty, distinct algorithms, innovative application, medium-term mining logistics planning problem, mine-to-client supply chain planning, mining industry, planning, supply chains

Identifiers

Local EPrints ID: 445784
URI: http://eprints.soton.ac.uk/id/eprint/445784
PURE UUID: 15fdfb35-f591-424e-badf-e058303ae93d
ORCID for E. F. Arruda: ORCID iD orcid.org/0000-0002-9835-352X

Catalogue record

Date deposited: 07 Jan 2021 17:33
Last modified: 28 Apr 2022 02:31

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Contributors

Author: J. M. Leal Gomes Leite
Author: E. F. Arruda ORCID iD
Author: L. Bahiense
Author: L. G. Marujo

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