A methodology for truck allocation problems considering dynamic circumstances in open pit mines, case study of the Sungun copper mine

Authors

  • Amin Moniri-Morad Sahand University of Technology
  • Mohammad Pourgol-Mohammad Sahand University of Technology
  • Hamid Aghababaei Sahand University of Technology
  • Javad Sattarvand University of Nevada, Reno

DOI:

https://doi.org/10.17794/rgn.2019.4.6

Keywords:

haul truck allocation, optimization, discrete-event simulation, production capacity

Abstract

Truck allocation problems are considered as one of the most substantial factors in the achievement of planned produc- tion capacity in the mining industry. Traditional truck allocation techniques (e.g. mathematical programming, queueing theories) have undergone different levels of simplifications in formulating actual haulage operations under heterogene- ous circumstances. In this study, the truck allocation problem is analysed through the development of the simulation- based optimization (SBO) method for the optimization of truck assignment considering uncertainties during fleet op- eration. This method provides an integrated structure by the simultaneous combination of optimization and stochastic discrete-event simulation. The objective function is to minimize the total number of trucks for haulage operation with discrete-event simulation employed to model the constraints. As a case study, the fleet operation of the Sungun copper mine is investigated to accomplish an optimal truck allocation for various working benches in the mine site. Operation details are evaluated through different indicators such as utilization, waiting times, and the amount of transported ma- terials for each working bench. Finally, the operation bottlenecks are recognized for each situation.

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Published

2019-09-21

How to Cite

Moniri-Morad, A., Pourgol-Mohammad, M., Aghababaei, H., & Sattarvand, J. (2019). A methodology for truck allocation problems considering dynamic circumstances in open pit mines, case study of the Sungun copper mine. Rudarsko-geološko-Naftni Zbornik, 34(4). https://doi.org/10.17794/rgn.2019.4.6

Issue

Vol. 34 No. 4 (2019): No. 47

Section

Mining

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