Optimization of truck-shovel allocation in open-pit mines under uncertainty: a chance-constrained goal programming approach. Issue 2 (3rd April 2021)

• Record Type: Journal Article
• Authors: Mohtasham, Mehrnaz; Mirzaei-Nasirabad, Hossein; Alizadeh, Behrooz
• Is Part Of: Mining technology. Volume 130:Issue 2(2021)
• Page Start: 81
• Page End: 100
• Publication Date: 2021-04-03
• Subjects: Open-pit mining -- optimization -- truck allocation uncertainty -- chance-constrained goal programming; Mining engineering -- Periodicals; Mineral industries -- Periodicals; 662.05; 622.05
• DOI: 10.1080/25726668.2021.1916170
• Languages: English
• ISSNs: 2572-6668

Abstract

ABSTRACT: The truck allocation problem is an important section of the transportation system in open-pit mines. Most available models for the truck scheduling problem do not directly address the stochastic nature of truck-shovel systems by using multi-objective optimization techniques. This paper presents a chance-constrained goal programming (CCGP) model based on four important goals to estimate the impacts of the uncertainty on the efficiency of truck-shovel systems. The proposed model has been implemented using 11 schedule scenarios and different confidence levels (CLs) for loader's production to determine the best allocation of trucks in an open-pit copper mine. The results display that the model can handle the quality and quantity of material required to achieve the objectives of the short-term production schedule of the mine in all CLs, even in the highest risk level. This model has a remarkable ability to meet the required objectives in terms of uncertainty in mining operations.