Long-term mine production scheduling with multiple processing destinations under mineral supply uncertainty,based on multi-neighbourhood Tabu search

ABSTRACT

This paper presents a new mathematical formulation to address mine production scheduling with multiple processing streams, under mineral supply uncertainty, and where the destination is formulated as a variable for each block. The proposed mathematical model maximises discounted cash flows and penalises deviations from production targets. A parallel multi-neighbourhood Tabu search metaheuristic is developed to optimise the proposed model. An application at a gold deposit shows the practical aspects and computational efficiency of the model, as well as its ability to provide a schedule that meets production targets and provides a stable destination feed in term of tonnage.     

Genetic algorithm to simultaneously optimise stope sequencing and equipment dispatching in underground short-term mine planning under time uncertainty

ABSTRACT

The main issue in short-term planning optimisation for underground mining is organising the mining process with limited resources in the form of equipment and materials to satisfy production targets and stable feed grade requirements. In this paper, an integrated optimisation model is proposed based on an individual generation algorithm and an improved Genetic Algorithm to simultaneously optimise stope extraction sequencing and timing, extracted ore grade and equipment dispatching. The model objectives are to shorten the time gap between the stope mining processes and the overall working time. When the uncertainty of equipment working time is taken into account in a short-term scheduling model, the Monte Carlo simulation is applied to evaluate the risk of not meeting the production target. A modification strategy is defined to evaluate equipment failure. Consequently, any available equipment is automatically reassigned to the mining site to replace the broken-down equipment. A case study is used to validate the model in the Sanshandao gold mine of China to formulate an optimal monthly schedule. Compared with the conventional approach, the new model could reduce the variance of ore tonnage and feed grade and improve the equipment allocation efficiency. Discussions are presented to address the uncertainty.     

Stochastic optimisation of long-term block cave scheduling with hang-up and grade uncertainty

Abstract

Mass mining methods provide alternatives in developing deeper and lower-grade mineral deposits. Consequently, block cave mining has been increasingly popular mass mining method, especially for large copper deposits currently being mined by open pit methods. This study adopts similar concepts as in stochastic open pit production planning to the planning of block cave mines, to evaluate their effectiveness in a different approach to mass mining. The main contribution of this study is the incorporation of the uncertainty of delays from hang-ups and grades directly into the production scheduling process of a cave mining operation. Hang-up uncertainty relates to the uncertainty linked to the occurrence of ore that clogs the production draw points. This clogging causes time delays in the production cycle leading to tonnage losses and additional costs. Grade uncertainty is incorporated by means of stochastic orebody simulations. Both uncertainty sources are directly linked to the extraction decisions and influence the optimized schedules. The proposed stochastic integer programming model is applied to the optimization of the long-term schedule of a large-scale, low-grade copper deposit by taking into account hang-up delays in block caving. The results of the optimization maximizing net present value clearly show the capability of the formulation to mitigate the effects of both grade and hang-up uncertainty.