Development of a goal programming model for optimization of truck allocation in open pit mines

Abstract

Truck and shovel operations comprise approximately 60% of the total operating costs in open pit mines. In order to increase productivity and reduce the cost of mining operations, it is essential to manage the equipment used with high efficiency. In this work, the chance-constrained goal programing (CCGP) model presented by Michalakopoulos and Panagiotou is developed to determine an optimal truck allocation plan in open pit mines and reduce the waiting times of trucks and shovels. The developed goal programming (GP) model is established considering four desired goals: “maximizing shovel production", “minimizing deviations in head grade", “minimizing deviations in tonnage feed to the processing plants from the desired feed" and “minimizing truck operating costs". To employ the developed model, a software is prepared in Visual Studio with C# programming language. In this computer program, the CPLEX optimizer software is incorporated for solving the developed goal programing model. The case study of Sungun copper mine is also considered to evaluate the presented GP model and prepared software. The results obtained indicate that the developed model increases the mine production above 20.6% with respect to the traditional truck allocation plan, while meeting the desired grade and the stripping ratio constraints.