Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Integrating mining loading and hauling equipment selection and replacement decisions using stochastic linear programming
Department of Mining Engineering, Pontificia Universidad Católica de Chile, Santiago.
Pontificia Universidad Católica de Chile, Department of Mining Engineering, Pontificia Universidad Católica de Chile, Santiago.
Department of Engineering Sciences, Universidad Andres Bello, Santiago.
Department of Industrial Engineering, Pontificia Universidad Católica de Chile, Santiago.
Show others and affiliations
Number of Authors: 52017 (English)In: International Journal of Mining, Reclamation and Environment, ISSN 1748-0930, E-ISSN 1748-0949, Vol. 31, no 1, p. 52-65Article in journal (Refereed) Published
Abstract [en]

Equipment selection is a key strategic decision in the design of a material handling system, because an improper one will lead to operational problems and unnecessary investment costs. It involves determining the number and combination of loaders and trucks which will move the material, fulfilling a specified production schedule. Previous works have addressed this problem with deterministic approaches, without considering the inter-dependent availability of trucks and loaders. In order to fill this gap, we developed a stochastic model that combines the selection and equipment replacement problems, subject to a stochastic production rate constraint. This is a new idea that will help decision-makers to decide faster and more reliable. The proposed model optimises the fleet by minimising the total life cycle costs. To solve it, we used a linearisation approach that reduces the computational effort. We tested our approach with a benchmark model, using a mining case study. Results indicate that the solutions ensure with a high probability a determined production target, producing good robust solutions compared to the deterministic counterpart.

Place, publisher, year, edition, pages
Taylor & Francis, 2017. Vol. 31, no 1, p. 52-65
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-5660DOI: 10.1080/17480930.2015.1115589ISI: 000392223100004Scopus ID: 2-s2.0-84949184007Local ID: 3d33d2ed-31c0-4bdb-9c4b-f8e0e0e02d9dOAI: oai:DiVA.org:ltu-5660DiVA, id: diva2:978534
Note

Validerad; 2017; Nivå 2; 2017-01-17 (andbra)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-11-15Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Galar, Diego

Search in DiVA

By author/editor
Galar, Diego
By organisation
Operation, Maintenance and Acoustics
In the same journal
International Journal of Mining, Reclamation and Environment
Other Civil Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 445 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf