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Joint stochastic short-term production scheduling and fleet management optimization for mining complexes
- Source :
- Optimization and Engineering. 21:1717-1743
- Publication Year :
- 2020
- Publisher :
- Springer Science and Business Media LLC, 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.
- Subjects :
- Mathematical optimization
021103 operations research
Control and Optimization
Optimization problem
business.product_category
business.industry
Computer science
Mechanical Engineering
0211 other engineering and technologies
Scheduling (production processes)
Aerospace Engineering
Time horizon
02 engineering and technology
Production schedule
Stochastic optimization
Shovel
Electrical and Electronic Engineering
business
Metaheuristic
Software
021102 mining & metallurgy
Civil and Structural Engineering
Fleet management
Subjects
Details
- ISSN :
- 15732924 and 13894420
- Volume :
- 21
- Database :
- OpenAIRE
- Journal :
- Optimization and Engineering
- Accession number :
- edsair.doi...........836bff3afb0ef3eb6576e4f59e8afe3e
- Full Text :
- https://doi.org/10.1007/s11081-020-09495-x