Optimisation of a Mixed Truck Fleet Schedule through a MIP Model Considering a New Truck-Purchase Option

Mining is a capital-intensive industry that requires hundreds of million-dollar investment in major equipment. In regards to surface mining operations, mine trucks are the most common pieces of equipment that are used for material haulage. Their maintenance cost, however, constitutes a significant p...

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Main Authors: Fu, Z., Topal, Erkan, Erten, Oktay
Format: Journal Article
Published: Maney Publishing 2014
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/14197
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author Fu, Z.
Topal, Erkan
Erten, Oktay
author_facet Fu, Z.
Topal, Erkan
Erten, Oktay
author_sort Fu, Z.
building Curtin Institutional Repository
collection Online Access
description Mining is a capital-intensive industry that requires hundreds of million-dollar investment in major equipment. In regards to surface mining operations, mine trucks are the most common pieces of equipment that are used for material haulage. Their maintenance cost, however, constitutes a significant proportion of the overall operational cost. Currently available costing methods and models do not take into account all key constraints and as a result, maintenance cost cannot be minimised. A new mixed integer programming (MIP) model is developed to minimise the maintenance cost for a heterogeneous truck fleet over a multi-year period while considering a new truck-purchase option. The proposed model is applied to truck maintenance cost data from a gold mine in Western Australia. Results indicate 21.64% and 14.76% cost savings over 10 years in comparison to the spread sheet based and original MIP models, respectively.
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spelling curtin-20.500.11937-141972017-09-13T15:58:09Z Optimisation of a Mixed Truck Fleet Schedule through a MIP Model Considering a New Truck-Purchase Option Fu, Z. Topal, Erkan Erten, Oktay Mixed integer programming Mine optimisation Mine truck scheduling Cost minimisation Mining is a capital-intensive industry that requires hundreds of million-dollar investment in major equipment. In regards to surface mining operations, mine trucks are the most common pieces of equipment that are used for material haulage. Their maintenance cost, however, constitutes a significant proportion of the overall operational cost. Currently available costing methods and models do not take into account all key constraints and as a result, maintenance cost cannot be minimised. A new mixed integer programming (MIP) model is developed to minimise the maintenance cost for a heterogeneous truck fleet over a multi-year period while considering a new truck-purchase option. The proposed model is applied to truck maintenance cost data from a gold mine in Western Australia. Results indicate 21.64% and 14.76% cost savings over 10 years in comparison to the spread sheet based and original MIP models, respectively. 2014 Journal Article http://hdl.handle.net/20.500.11937/14197 10.1179/1743286314Y.0000000055 Maney Publishing restricted
spellingShingle Mixed integer programming
Mine optimisation
Mine truck scheduling
Cost minimisation
Fu, Z.
Topal, Erkan
Erten, Oktay
Optimisation of a Mixed Truck Fleet Schedule through a MIP Model Considering a New Truck-Purchase Option
title Optimisation of a Mixed Truck Fleet Schedule through a MIP Model Considering a New Truck-Purchase Option
title_full Optimisation of a Mixed Truck Fleet Schedule through a MIP Model Considering a New Truck-Purchase Option
title_fullStr Optimisation of a Mixed Truck Fleet Schedule through a MIP Model Considering a New Truck-Purchase Option
title_full_unstemmed Optimisation of a Mixed Truck Fleet Schedule through a MIP Model Considering a New Truck-Purchase Option
title_short Optimisation of a Mixed Truck Fleet Schedule through a MIP Model Considering a New Truck-Purchase Option
title_sort optimisation of a mixed truck fleet schedule through a mip model considering a new truck-purchase option
topic Mixed integer programming
Mine optimisation
Mine truck scheduling
Cost minimisation
url http://hdl.handle.net/20.500.11937/14197