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Mixed–Integer Linear Programming formulation for block–cave sequence optimisation

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Relying only on manual planning methods or computer software based on heuristic algorithms will lead to mine schedules that are not the optimal global solution. The objective of this paper is to develop a practical optimisation framework to schedule production for caving operations. We present two Mixed–Integer Linear Programming (MILP) formulations for the long–term production scheduling of block caving. First, we solve the problem at the drawpoint level. Then, we aggregate drawpoints into larger units referred to as clusters. The formulations are developed, implemented and verified in the TOMLAB/CPLEX environment. The production scheduler aims to maximise the Net Present Value (NPV) of the mining operation while the mine planner has control over the development rate, vertical mining rate, lateral mining rate, mining capacity, maximum number of active drawpoints and advancement direction. Application and comparison of the models for production scheduling using real mine data over 15 periods are presented.

Keywords: block caving, mixed integer linear programming, MILP, production scheduling, aggregation, CPLEX, mine schedules, mining, optimisation

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