Joint stochastic short-term production scheduling and fleet management optimization for mining complexes
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Joint stochastic short‑term production scheduling and fleet management optimization for mining complexes Christian Both1 · Roussos Dimitrakopoulos1 Received: 8 May 2019 / Revised: 4 March 2020 / Accepted: 4 March 2020 © The Author(s) 2020
Abstract This article presents a novel stochastic optimization model that simultaneously optimizes the short-term extraction sequence, shovel relocation, scheduling of a heterogeneous hauling fleet, and downstream allocation of extracted materials in open-pit mining complexes. The proposed stochastic optimization formulation considers geological uncertainty in addition to uncertainty related to equipment performances and truck cycle times. The method is applied at a real-world mining complex, stressing the benefits of optimizing the short-term production schedule and fleet management simultaneously. Compared to a conventional two-step approach, where the production schedule is optimized first before optimizing the allocation of the mining fleet, the costs generated by shovel movements are reduced by 56% and lost production due to shovel relocation is cut by 54%. Furthermore, the required number of trucks shows a more balanced profile, reducing total truck operational costs by 3.1% over an annual planning horizon, as well as the required haulage capacity in the most haulage-intense periods by 25%. A metaheuristic solution method is utilized to solve the large optimization problem in a reasonable timespan. Keywords Short-term mine planning · Production scheduling · Fleet management · Stochastic mixed integer programming · Metaheuristics
1 Introduction Short-term mine planning generally aims to make optimal decisions over a timeframe of days to months to best meet annual production targets given by the longterm mine production plan (Wilke and Reimer 1977; Fytas et al. 1987; Hustrulid et al. 2013). This task is typically accomplished in two separate steps. In the first * Christian Both [email protected] 1
COSMO – Stochastic Mine Planning Laboratory, Department of Mining and Materials Engineering, McGill University, FDA Building, 3450 University Street, Montreal, QC H3A 0E8, Canada
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step, the physical short-term extraction sequence is optimized, which is guided by the long-term mine plan and other pertinent short-term objectives (Blom et al. 2018). The second step optimizes the assignment of mining equipment (trucks and shovels) in open pit mines and is referred to as fleet management (Afrapoli and Askari-Nasab 2017). Fleet management optimization includes two parts. The first part optimizes the shovel positions in the mine as well as the allocation of a certain number of trucks to the related shovels. The second part optimizes truck dispatching to allocate single trucks to their next destination (Alarie and Gamache 2002; Afrapoli and Askari-Nasab 2017). Note that shovels are typically large in size to facilitate the cost-efficient extraction of materials, which leads to their difficult and costly relocatio
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