Joint stochastic short-term production scheduling and fleet management optimization for mining complexes

被引:0
作者
Christian Both
Roussos Dimitrakopoulos
机构
[1] McGill University,COSMO – Stochastic Mine Planning Laboratory, Department of Mining and Materials Engineering
来源
Optimization and Engineering | 2020年 / 21卷
关键词
Short-term mine planning; Production scheduling; Fleet management; Stochastic mixed integer programming; Metaheuristics;
D O I
暂无
中图分类号
学科分类号
摘要
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.
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页码:1717 / 1743
页数:26
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