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Long term production planning of open pit mines by ant colony optimization

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  • Shishvan, Masoud Soleymani
  • Sattarvand, Javad

Abstract

The problem of long-term production planning of open pit mines is a large combinatorial problem. Application of mathematical programming approaches suffer from reduced computational efficiency due to the large amount of decision variables. This paper presents a new metaheuristic approximation approach based on the Ant Colony Optimization (ACO) for the solution of the problem of open-pit mine production planning. It is a three-dimensional optimization procedure which has the capability of considering any type of objective function, non-linear constraints and real technical restrictions. The proposed process is programmed and tested through its application on a real scale Copper–Gold deposit. The study revealed that the ACO approach is capable to improve the value of the initial mining schedule regarding the current commercial tools considering penalties and without, in a reasonable computational time. Several variants of ACO were examined to find the most compatible variants and the best parameter ranges. Results indicated that the Max–Min Ant System (MMAS) and the Ant Colony System (ACS) are the best possible variants based on the required less amount of memory. It is also proved that the MMAS is the most explorative variant, while the ACS is the fastest method.

Suggested Citation

  • Shishvan, Masoud Soleymani & Sattarvand, Javad, 2015. "Long term production planning of open pit mines by ant colony optimization," European Journal of Operational Research, Elsevier, vol. 240(3), pages 825-836.
    • Handle: RePEc:eee:ejores:v:240:y:2015:i:3:p:825-836
    DOI: 10.1016/j.ejor.2014.07.040
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    1. 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.
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    2. 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.
    3. Paithankar, Amol & Chatterjee, Snehamoy & Goodfellow, Ryan & Asad, Mohammad Waqar Ali, 2020. "Simultaneous stochastic optimization of production sequence and dynamic cut-off grades in an open pit mining operation," Resources Policy, Elsevier, vol. 66(C).
    4. Jann Michael Weinand & Kenneth Sorensen & Pablo San Segundo & Max Kleinebrahm & Russell McKenna, 2020. "Research trends in combinatorial optimisation," Papers 2012.01294, arXiv.org.
    5. Alipour, Aref & Khodaiari, Ali Asghar & Jafari, Ahmad & Tavakkoli-Moghaddam, Reza, 2022. "An integrated approach to open-pit mines production scheduling," Resources Policy, Elsevier, vol. 75(C).
    6. Samavati, Mehran & Essam, Daryl & Nehring, Micah & Sarker, Ruhul, 2017. "A local branching heuristic for the open pit mine production scheduling problem," European Journal of Operational Research, Elsevier, vol. 257(1), pages 261-271.
    7. Savolainen, Jyrki, 2016. "Real options in metal mining project valuation: Review of literature," Resources Policy, Elsevier, vol. 50(C), pages 49-65.
    8. Amin Mousavi & Erhan Kozan & Shi Qiang Liu, 2016. "Comparative analysis of three metaheuristics for short-term open pit block sequencing," Journal of Heuristics, Springer, vol. 22(3), pages 301-329, June.
    9. Moreno, Eduardo & Rezakhah, Mojtaba & Newman, Alexandra & Ferreira, Felipe, 2017. "Linear models for stockpiling in open-pit mine production scheduling problems," European Journal of Operational Research, Elsevier, vol. 260(1), pages 212-221.
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    12. 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.
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    14. Jovanovic, Raka & Tuba, Milan & Voß, Stefan, 2019. "An efficient ant colony optimization algorithm for the blocks relocation problem," European Journal of Operational Research, Elsevier, vol. 274(1), pages 78-90.
    15. King, Barry & Goycoolea, Marcos & Newman, A., 2017. "Optimizing the open pit-to-underground mining transition," European Journal of Operational Research, Elsevier, vol. 257(1), pages 297-309.
    16. Zheng, Xiaolei & Nguyen, Hoang & Bui, Xuan-Nam, 2021. "Exploring the relation between production factors, ore grades, and life of mine for forecasting mining capital cost through a novel cascade forward neural network-based salp swarm optimization model," Resources Policy, Elsevier, vol. 74(C).
    17. Samavati, Mehran & Essam, Daryl & Nehring, Micah & Sarker, Ruhul, 2017. "A methodology for the large-scale multi-period precedence-constrained knapsack problem: an application in the mining industry," International Journal of Production Economics, Elsevier, vol. 193(C), pages 12-20.
    18. Chatterjee, Snehamoy & Sethi, Manas Ranjan & Asad, Mohammad Waqar Ali, 2016. "Production phase and ultimate pit limit design under commodity price uncertainty," European Journal of Operational Research, Elsevier, vol. 248(2), pages 658-667.
    19. Jiang Yao & Zhiqiang Wang & Hongbin Chen & Weigang Hou & Xiaomiao Zhang & Xu Li & Weixing Yuan, 2023. "Open-Pit Mine Truck Dispatching System Based on Dynamic Ore Blending Decisions," Sustainability, MDPI, vol. 15(4), pages 1-12, February.

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