IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v13y2025i11p1843-d1669576.html
   My bibliography  Save this article

Multi-Objective Ore Blending Optimization for Polymetallic Open-Pit Mines Based on Improved Matter-Element Extension Model and NSGA-II

Author

Listed:
  • Jun Xiang

    (School of Resources and Safety Engineering, Central South University, Changsha 410083, China
    Guangdong Province Dabaoshan Mining Co., Ltd., Shaoguan 512127, China)

  • Jianhong Chen

    (School of Resources and Safety Engineering, Central South University, Changsha 410083, China)

  • Aishu Zhang

    (Guangdong Province Dabaoshan Mining Co., Ltd., Shaoguan 512127, China)

  • Xing Zhao

    (Guangdong Province Dabaoshan Mining Co., Ltd., Shaoguan 512127, China)

  • Shengyuan Zhuo

    (School of Resources and Safety Engineering, Central South University, Changsha 410083, China)

  • Shan Yang

    (School of Resources and Safety Engineering, Central South University, Changsha 410083, China)

Abstract

With the increasing demand for mineral resources, sustainable mining development faces challenges such as low resource utilization efficiency. Ore blending optimization has emerged as a critical approach to enhance resource utilization. This study constructs a multi-objective ore blending optimization system for complex polymetallic open-pit mines based on the improved matter-element extension model and NSGA-II algorithm. By identifying key blending factors, objective functions are established to minimize both total ore quantity deviation and grade deviation, with six constraints defined to reflect production capacity limits. The NSGA-II algorithm is employed to solve the multi-objective optimization problem, generating a Pareto optimal solution set from which the optimal ore blending scheme is selected using the improved matter-element extension model. A case verification at Dabaoshan Mine demonstrates that the model-verified scheme achieves 1.035% higher total production accuracy than the planned value and 2.828% higher than actual production, while improving Cu grade deviation accuracy by 7.021% over the plan and 1.064% over actual production, and S grade deviation accuracy by 33.027% over the plan and 3.127% over actual production. This study, through the construction of systematic ore blending theory and empirical analysis, provides an important theoretical framework and methodological support for subsequent research on ore blending in polymetallic open-pit mines. It demonstrates significant practical application value in Dabaoshan Mine, offering an intelligent mine solution that combines scientific rationality and engineering practicability for polymetallic open-pit mines.

Suggested Citation

  • Jun Xiang & Jianhong Chen & Aishu Zhang & Xing Zhao & Shengyuan Zhuo & Shan Yang, 2025. "Multi-Objective Ore Blending Optimization for Polymetallic Open-Pit Mines Based on Improved Matter-Element Extension Model and NSGA-II," Mathematics, MDPI, vol. 13(11), pages 1-17, May.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:11:p:1843-:d:1669576
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/13/11/1843/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/13/11/1843/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Amina Lamghari & Roussos Dimitrakopoulos & Jacques A Ferland, 2014. "A variable neighbourhood descent algorithm for the open-pit mine production scheduling problem with metal uncertainty," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(9), pages 1305-1314, September.
    2. Mancini, Lucia & Sala, Serenella, 2018. "Social impact assessment in the mining sector: Review and comparison of indicators frameworks," Resources Policy, Elsevier, vol. 57(C), pages 98-111.
    3. Lu Chen & Qinghua Gu & Rui Wang & Zhidong Feng & Chao Zhang, 2022. "Comprehensive Utilization of Mineral Resources: Optimal Blending of Polymetallic Ore Using an Improved NSGA-III Algorithm," Sustainability, MDPI, vol. 14(17), pages 1-19, August.
    4. Iqbal, Shahid A. & Raj, Saurav & Shiva, Chandan Kumar, 2025. "A chaotic chimp sine cosine algorithm for optimizing hydrothermal power scheduling," Chaos, Solitons & Fractals, Elsevier, vol. 192(C).
    5. Shuyu Li & Rongrong Li, 2019. "Evaluating Energy Sustainability Using the Pressure-State-Response and Improved Matter-Element Extension Models: Case Study of China," Sustainability, MDPI, vol. 11(1), pages 1-20, January.
    6. Shan Yang & Shengyuan Zhuo & Zitong Xu & Jianhong Chen, 2023. "Risk Assessment of Mining Heritage Reuse in Public–Private-Partnership Mode Based on Improved Matter–Element Extension Model," Mathematics, MDPI, vol. 11(16), pages 1-18, August.
    7. 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.
    8. Shan Yang & Zitong Xu & Kaijun Su, 2021. "Variable Weight Matter–Element Extension Model for the Stability Classification of Slope Rock Mass," Mathematics, MDPI, vol. 9(21), pages 1-13, November.
    9. 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.
    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. 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.
    2. 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.
    3. Lin, Jingsi & Asad, Mohammad Waqar Ali & Topal, Erkan & Chang, Ping & Huang, Jinxin & Lin, Wei, 2024. "A novel model for sustainable production scheduling of an open-pit mining complex considering waste encapsulation," Resources Policy, Elsevier, vol. 91(C).
    4. 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).
    5. Van Assche, Kristof & Gruezmacher, Monica & Granzow, Michael, 2021. "From trauma to fantasy and policy. The past in the futures of mining communities; the case of Crowsnest Pass, Alberta," Resources Policy, Elsevier, vol. 72(C).
    6. 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.
    7. Christina G. Siontorou, 2023. "Fair Development Transition of Lignite Areas: Key Challenges and Sustainability Prospects," Sustainability, MDPI, vol. 15(16), pages 1-14, August.
    8. Guzmán, Juan Ignacio & Karpunina, Alina & Araya, Constanza & Faúndez, Patricio & Bocchetto, Marcela & Camacho, Rodolfo & Desormeaux, Daniela & Galaz, Juanita & Garcés, Ingrid & Kracht, Willy & Lagos, , 2023. "Chile: On the road to global sustainable mining," Resources Policy, Elsevier, vol. 83(C).
    9. 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.
    10. Shaofeng Wang & Xin Cai & Jian Zhou & Zhengyang Song & Xiaofeng Li, 2022. "Analytical, Numerical and Big-Data-Based Methods in Deep Rock Mechanics," Mathematics, MDPI, vol. 10(18), pages 1-5, September.
    11. Yıldız, Taşkın Deniz & Kural, Orhan, 2020. "The effects of the mining operation activities permit process on the mining sector in Turkey," Resources Policy, Elsevier, vol. 69(C).
    12. Kamyar Tolouei & Ehsan Moosavi & Mehran Gholinejad, 2024. "Solving LTPSOP in open-pit mines using Gaussian process and human mental search," OPSEARCH, Springer;Operational Research Society of India, vol. 61(3), pages 1061-1092, September.
    13. Fernandez, Viviana, 2021. "Are extractive ventures more socio-environmentally committed?," Resources Policy, Elsevier, vol. 74(C).
    14. Shuangyan Guo & Shan Yang & Canjiao Liu, 2024. "Mining Heritage Reuse Risks: A Systematic Review," Sustainability, MDPI, vol. 16(10), pages 1-16, May.
    15. V. L. Morgan & E. S. McLamore & M. Correll & G. A. Kiker, 2021. "Emerging mercury mitigation solutions for artisanal small-scale gold mining communities evaluated through a multicriteria decision analysis approach," Environment Systems and Decisions, Springer, vol. 41(3), pages 413-424, September.
    16. Heydari, Mehrnoosh & Osanloo, Morteza & Başçetin, Ataç, 2023. "Developing a new social impact assessment model for deep open-pit mines," Resources Policy, Elsevier, vol. 82(C).
    17. Angelo Antoci & Paolo Russu & Elisa Ticci, 2019. "Mining and Local Economies: Dilemma between Environmental Protection and Job Opportunities," Sustainability, MDPI, vol. 11(22), pages 1-21, November.
    18. Jélvez, Enrique & Morales, Nelson & Nancel-Penard, Pierre & Cornillier, Fabien, 2020. "A new hybrid heuristic algorithm for the Precedence Constrained Production Scheduling Problem: A mining application," Omega, Elsevier, vol. 94(C).
    19. Fox, Sarah Jane, 2022. "‘Exploiting – land, sea and space: Mineral superpower’ In the name of peace: A critical race to protect the depths and heights," Resources Policy, Elsevier, vol. 79(C).
    20. Zhang, Zhimin & Elshkaki, Ayman, 2022. "An analysis of the supply-side factors of geological exploration in China based on provincial panel data between 1999 and 2017," Resources Policy, Elsevier, vol. 76(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:gam:jmathe:v:13:y:2025:i:11:p:1843-:d:1669576. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.