Abstract
SYNOPSIS Operational mine planning is a fundamental activity in mine operations and should take into account various characteristics of the material, the available mining faces, the requirements of discharge points, and production hiatuses due to reduced equipment operational efficiency, in order to efficiently allocate shovels and trucks and deliver the required tonnage and quality to the proper destinations. This paper presents an approach for optimizing short-term day-to-day mining operations using simulation. A mathematical model based on integer linear programming is developed. The solution is obtained through two different software packages using discrete event simulation (Arena) and a mathematical optimization model (Lingo). The two integrated models search an efficient solution to optimize a set of criteria by applying goal programming to hierarchically optimize five objective functions in a logical priority order under the operator's standpoint and by simulating mining operations and unproductive events to evaluate how closely the optimized results are actually achieved. The integrated models are applied to a real large-scale iron ore mine in southeastern Brazil. A decision support system (DSS) prototype that meets the production requirements is also applied. The results show that an increase in the available loading equipment will not result necessarily in increased production, as expected. The models show satisfactory results and applicability to real and complex mining situations, and the formulation allows for easy adaptation to other mine situations. Keywords: discrete event simulation, optimization, decision support system, mine planning, linear programming.
Highlights
Mine planning involves solving complex problems while taking into consideration various parameters and events that may arise through the life of mine
Short-term and operational planning in open pit mines are recurrent problems solved by different methodologies, including linear programming (LP), mixed integer linear programming (MILP), heuristics and metaheuristics, stochastic optimization, and by applying simulation combined with other mathematical programming techniques
This paper presents a solution for the short-term mine planning problem through the techniques of optimization and simulation
Summary
Mine planning involves solving complex problems while taking into consideration various parameters and events that may arise through the life of mine Mining problems such as truck and shovel allocation, ore blending, pit optimization, multi-pit mining, and multiple destinations, etc., are very complex problems that depend on various operational factors, classified as NP-hard problems (Fioroni et al, 2008; Souza et al, 2010; Thiruvady, Ernst, and Singh, 2014; Patterson, Kozan, and Hyland, 2017; Samavati et al, 2017). Short-term and operational planning in open pit mines are recurrent problems solved by different methodologies, including linear programming (LP), mixed integer linear programming (MILP), heuristics and metaheuristics, stochastic optimization, and by applying simulation combined with other mathematical programming techniques
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