Integrating mining loading and hauling equipment selection and replacement decisions using stochastic linear programming

Gabriel Santelices, Rodrigo Pascual, Armin Lüer-Villagra, Alejandro Mac Cawley, Diego Galar

Resultado de la investigación: Article

3 Citas (Scopus)

Resumen

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.

Idioma originalEnglish
Páginas (desde-hasta)52-65
Número de páginas14
PublicaciónInternational Journal of Mining, Reclamation and Environment
Volumen31
N.º1
DOI
EstadoPublished - 2 ene 2017

Huella dactilar

linear programing
Linear programming
Loaders
replacement
Trucks
Materials handling
Stochastic models
Linearization
cost
Costs
Life cycle
life cycle
Availability
decision
Replacement
material

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Geology
  • Earth-Surface Processes
  • Management of Technology and Innovation

Citar esto

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abstract = "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.",
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Integrating mining loading and hauling equipment selection and replacement decisions using stochastic linear programming. / Santelices, Gabriel; Pascual, Rodrigo; Lüer-Villagra, Armin; Mac Cawley, Alejandro; Galar, Diego.

En: International Journal of Mining, Reclamation and Environment, Vol. 31, N.º 1, 02.01.2017, p. 52-65.

Resultado de la investigación: Article

TY - JOUR

T1 - Integrating mining loading and hauling equipment selection and replacement decisions using stochastic linear programming

AU - Santelices, Gabriel

AU - Pascual, Rodrigo

AU - Lüer-Villagra, Armin

AU - Mac Cawley, Alejandro

AU - Galar, Diego

PY - 2017/1/2

Y1 - 2017/1/2

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AB - 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.

KW - equipment replacement

KW - Equipment selection

KW - linear stochastic programming

KW - mining industry

KW - production assurance

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