A stochastic hybrid simulation-optimization approach towards haul fleet sizing in surface mines

Ali Moradi Afrapoli, Mohammad Tabesh, Hooman Askari-Nasab

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Haul fleet size determination is a critical task in any surface mining operation where the material is handled using the truck-and-shovel system. Although the problem of finding the optimum haulage fleet size has been thoroughly studied, there are two important shortcomings: disregarding the effects of downstream processes on the operation and ignoring the fleet management system effects. This paper presents an integrated simulation-optimization framework to address the haul fleet size determination problem surface mines and target the two shortcomings listed above. In the developed framework, the mining operation, the processing plants, and the operational decision tools communicate with each other to find the best size of the haul fleet required to meet the production schedule. Results of the study show that the developed framework is capable of handling the operation with 13% less number of trucks than the required number of trucks suggested by deterministic calculations.

Original languageEnglish
Pages (from-to)9-20
Number of pages12
JournalMining Technology: Transactions of the Institute of Mining and Metallurgy
Volume128
Issue number1
DOIs
StatePublished - Jan 2 2019

Bibliographical note

Publisher Copyright:
© 2018, © 2018 Institute of Materials, Minerals and Mining and The AusIMM Published by Taylor & Francis on behalf of the Institute and The AusIMM.

Keywords

  • fleet management
  • haul fleet sizing
  • optimization
  • Simulation
  • surface mining
  • truck dispatching

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Geology

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