IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v79y2022ics0301420722003944.html
   My bibliography  Save this article

Model and algorithms applied to Short-Term Integrated Programming Problem in Mines

Author

Listed:
  • Menezes, Gustavo Campos
  • dos Santos Corrêa, Juliano

Abstract

Mineral extraction is a significantly impacted activity. In several countries, this contribution of mineral extraction is very relevant due to the global scales of mining assets in the soil. Large mining companies have multiple productive and logistic resources, and one integrated planning is necessary to optimize these assets and reduce operating costs. In this context, this paper considers integrated short-term programming in open-pit mines. The main contribution of this work is a mathematical model that considers quality, metallurgical recovery for processing plants, mass balance, and inventory control (storage yard) in an integrated approach. Besides the mathematical model, another contribution is the set of algorithms projected to solve the integrated model (Relax and Fix, Fix and Optimize, and Local Branching). Several analyses were made to validate the mathematical model and algorithms, such as variations in supply and demand and adaptations related to the production capacity of the mining complex. The computational results demonstrate the quality of the solutions for various existing scenarios in a mining complex. As a result, the constructed solution approach (model and algorithms) proved to be satisfactory and capable of acting as a decision support tool for an iron ore mining complex.

Suggested Citation

  • Menezes, Gustavo Campos & dos Santos Corrêa, Juliano, 2022. "Model and algorithms applied to Short-Term Integrated Programming Problem in Mines," Resources Policy, Elsevier, vol. 79(C).
    • Handle: RePEc:eee:jrpoli:v:79:y:2022:i:c:s0301420722003944
    DOI: 10.1016/j.resourpol.2022.102950
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420722003944
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2022.102950?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Pimentel, Bruno S. & Mateus, Geraldo R. & Almeida, Franklin A., 2013. "Stochastic capacity planning and dynamic network design," International Journal of Production Economics, Elsevier, vol. 145(1), pages 139-149.
    2. Yasrebi, Amir Bijan & Hezarkhani, Ardeshir & Afzal, Peyman, 2017. "Application of Present Value-Volume (PV-V) and NPV-Cumulative Total Ore (NPV-CTO) fractal modelling for mining strategy selection," Resources Policy, Elsevier, vol. 53(C), pages 384-393.
    3. Alexandra M. Newman & Enrique Rubio & Rodrigo Caro & Andrés Weintraub & Kelly Eurek, 2010. "A Review of Operations Research in Mine Planning," Interfaces, INFORMS, vol. 40(3), pages 222-245, June.
    4. Dillenberger, Christof & Escudero, Laureano F. & Wollensak, Artur & Zhang, Wu, 1994. "On practical resource allocation for production planning and scheduling with period overlapping setups," European Journal of Operational Research, Elsevier, vol. 75(2), pages 275-286, June.
    5. Florent Hernandez & Michel Gendreau & Ola Jabali & Walter Rei, 2019. "A local branching matheuristic for the multi-vehicle routing problem with stochastic demands," Journal of Heuristics, Springer, vol. 25(2), pages 215-245, April.
    6. Lamghari, Amina & Dimitrakopoulos, Roussos, 2016. "Progressive hedging applied as a metaheuristic to schedule production in open-pit mines accounting for reserve uncertainty," European Journal of Operational Research, Elsevier, vol. 253(3), pages 843-855.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. O’Sullivan, Dónal & Newman, Alexandra, 2015. "Optimization-based heuristics for underground mine scheduling," European Journal of Operational Research, Elsevier, vol. 241(1), pages 248-259.
    2. Noriega, Roberto & Pourrahimian, Yashar, 2022. "A systematic review of artificial intelligence and data-driven approaches in strategic open-pit mine planning," Resources Policy, Elsevier, vol. 77(C).
    3. Zeng, Lanyan & Liu, Shi Qiang & Kozan, Erhan & Corry, Paul & Masoud, Mahmoud, 2021. "A comprehensive interdisciplinary review of mine supply chain management," Resources Policy, Elsevier, vol. 74(C).
    4. Nelis, Gonzalo & Morales, Nelson & Jelvez, Enrique, 2023. "Optimal mining cut definition and short-term open pit production scheduling under geological uncertainty," Resources Policy, Elsevier, vol. 81(C).
    5. Franco-Sepúlveda, Giovanni & Del Rio-Cuervo, Juan Camilo & Pachón-Hernández, María Angélica, 2019. "State of the art about metaheuristics and artificial neural networks applied to open pit mining," Resources Policy, Elsevier, vol. 60(C), pages 125-133.
    6. Rafael Epstein & Marcel Goic & Andrés Weintraub & Jaime Catalán & Pablo Santibáñez & Rodolfo Urrutia & Raúl Cancino & Sergio Gaete & Augusto Aguayo & Felipe Caro, 2012. "Optimizing Long-Term Production Plans in Underground and Open-Pit Copper Mines," Operations Research, INFORMS, vol. 60(1), pages 4-17, February.
    7. M. Fattahi & M. Mahootchi & S. M. Moattar Husseini, 2016. "Integrated strategic and tactical supply chain planning with price-sensitive demands," Annals of Operations Research, Springer, vol. 242(2), pages 423-456, July.
    8. Amina Lamghari & Roussos Dimitrakopoulos & Jacques Ferland, 2015. "A hybrid method based on linear programming and variable neighborhood descent for scheduling production in open-pit mines," Journal of Global Optimization, Springer, vol. 63(3), pages 555-582, November.
    9. Sabet, Ehsan & Yazdani, Baback & Kian, Ramez & Galanakis, Kostas, 2020. "A strategic and global manufacturing capacity management optimisation model: A Scenario-based multi-stage stochastic programming approach," Omega, Elsevier, vol. 93(C).
    10. Lin, James T. & Chen, Tzu-Li & Chu, Hsiao-Ching, 2014. "A stochastic dynamic programming approach for multi-site capacity planning in TFT-LCD manufacturing under demand uncertainty," International Journal of Production Economics, Elsevier, vol. 148(C), pages 21-36.
    11. Fuentes, Manuel & Cadarso, Luis & Marín, Ángel, 2019. "A hybrid model for crew scheduling in rail rapid transit networks," Transportation Research Part B: Methodological, Elsevier, vol. 125(C), pages 248-265.
    12. Clavijo López, Christian & Crama, Yves & Pironet, Thierry & Semet, Frédéric, 2024. "Multi-period distribution networks with purchase commitment contracts," European Journal of Operational Research, Elsevier, vol. 312(2), pages 556-572.
    13. César Flores-Fonseca & Rodrigo Linfati & John Willmer Escobar, 2022. "Exact algorithms for production planning in mining considering the use of stockpiles and sequencing of power shovels in open-pit mines," Operational Research, Springer, vol. 22(3), pages 2529-2553, July.
    14. Christina N. Burt & Lou Caccetta, 2014. "Equipment Selection for Surface Mining: A Review," Interfaces, INFORMS, vol. 44(2), pages 143-162, April.
    15. W. Brian Lambert & Andrea Brickey & Alexandra M. Newman & Kelly Eurek, 2014. "Open-Pit Block-Sequencing Formulations: A Tutorial," Interfaces, INFORMS, vol. 44(2), pages 127-142, April.
    16. Laureano Escudero & Javier Salmeron, 2005. "On a Fix-and-Relax Framework for a Class of Project Scheduling Problems," Annals of Operations Research, Springer, vol. 140(1), pages 163-188, November.
    17. K. Sirinanda & M. Brazil & P. Grossman & J. Rubinstein & D. Thomas, 2016. "Gradient-constrained discounted Steiner trees II: optimally locating a discounted Steiner point," Journal of Global Optimization, Springer, vol. 64(3), pages 515-532, March.
    18. Ángel Marín, 2006. "Airport management: taxi planning," Annals of Operations Research, Springer, vol. 143(1), pages 191-202, March.
    19. Kristin Uggen & Marte Fodstad & Vibeke Nørstebø, 2013. "Using and extending fix-and-relax to solve maritime inventory routing problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(2), pages 355-377, July.
    20. Renaud Chicoisne & Daniel Espinoza & Marcos Goycoolea & Eduardo Moreno & Enrique Rubio, 2012. "A New Algorithm for the Open-Pit Mine Production Scheduling Problem," Operations Research, INFORMS, vol. 60(3), pages 517-528, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jrpoli:v:79:y:2022:i:c:s0301420722003944. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30467 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.