IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i4p3692-d1071328.html
   My bibliography  Save this article

Mining Method Optimization of Difficult-to-Mine Complicated Orebody Using Pythagorean Fuzzy Sets and TOPSIS Method

Author

Listed:
  • Shuai Li

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

  • Qi Huang

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

  • Boyi Hu

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

  • Jilong Pan

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

  • Junyu Chen

    (Zhejiang Suichang Gold Mine Co., Ltd., Lishui 323304, China)

  • Jianguo Yang

    (Zhejiang Suichang Gold Mine Co., Ltd., Lishui 323304, China)

  • Xinghui Zhou

    (Zhejiang Suichang Gold Mine Co., Ltd., Lishui 323304, China)

  • Xinmin Wang

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

  • Haoxuan Yu

    (Civil Engineering Discipline, School of Engineering, Monash University, Malaysia Campus, Bandar Sunway 47500, Malaysia)

Abstract

In Suichang gold mine, the altered rock type gold deposits were cut by faults and joint fissures, leading to complex resource endowment characteristics, large changes in occurrence, a serious complex of ore vein branches and great difficulty in mining. In order to select a suitable mining method for such a difficult and complicated orebody, a multi-factor and multi-index comprehensive evaluation system involving benefits, costs, safety and other aspects was constructed by using the Pythagorean fuzzy sets and TOPSIS method. Taking Suichang gold mine as an example, the weighted aggregation evaluation matrix was constructed, the closeness index of the four mining schemes were 0.8436, 0.3370, 0.4296 and 0.4334, and the mechanized upward horizontal layering method was determined as the optimal scheme. This method overcame the fuzzy comparison of economic and technical indicators directly, but converted them into corresponding fuzzy numbers to obtain accurate closeness index for optimization. The application of this method not only ensured a safe, efficient and environment-friendly mining effect, but also provided a reference for the optimization of the mining scheme of the severely branched composite orebody.

Suggested Citation

  • Shuai Li & Qi Huang & Boyi Hu & Jilong Pan & Junyu Chen & Jianguo Yang & Xinghui Zhou & Xinmin Wang & Haoxuan Yu, 2023. "Mining Method Optimization of Difficult-to-Mine Complicated Orebody Using Pythagorean Fuzzy Sets and TOPSIS Method," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:4:p:3692-:d:1071328
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/4/3692/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/4/3692/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wenguang Yang, 2020. "Ingenious Solution for the Rank Reversal Problem of TOPSIS Method," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-12, January.
    2. Haoxuan Yu & Shuai Li & Lifeng Yu & Xinmin Wang, 2022. "The Recent Progress China Has Made in Green Mine Construction, Part II: Typical Examples of Green Mines," IJERPH, MDPI, vol. 19(13), pages 1-14, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jahanbani, Zeinab & Ataee-pour, Majid & Mortazavi, Ali, 2024. "Application of Z-numbers theory to study the influencing criteria in underground mining method selection," Resources Policy, Elsevier, vol. 88(C).
    2. Jiayi Shen & Chenhao Sun & Huajie Huang & Jiawang Chen & Chuangzhou Wu, 2023. "Scale Effects on Shear Strength of Rough Rock Joints Caused by Normal Stress Conditions," Sustainability, MDPI, vol. 15(9), pages 1-14, May.

    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. Ozan Çakır & İbrahim Gürler & Bora Gündüzyeli, 2022. "Analysis of a Non-Discriminating Criterion in Simple Additive Weighting Deep Hierarchy," Mathematics, MDPI, vol. 10(17), pages 1-22, September.
    2. Liu, Quanlong & Qiu, Zunxiang & Li, Ma & Shang, Jianping & Niu, Weichao, 2023. "Evaluation and empirical research on green mine construction in coal industry based on the AHP-SPA model," Resources Policy, Elsevier, vol. 82(C).
    3. Haoxuan Yu & Izni Zahidi, 2023. "Tailings Pond Classification Based on Satellite Images and Machine Learning: An Exploration of Microsoft ML.Net," Mathematics, MDPI, vol. 11(3), pages 1-14, January.
    4. Hottenroth, H. & Sutardhio, C. & Weidlich, A. & Tietze, I. & Simon, S. & Hauser, W. & Naegler, T. & Becker, L. & Buchgeister, J. & Junne, T. & Lehr, U. & Scheel, O. & Schmidt-Scheele, R. & Ulrich, P. , 2022. "Beyond climate change. Multi-attribute decision making for a sustainability assessment of energy system transformation pathways," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    5. Maohui Ren & Tao Zhou & Di Wang & Chenxi Wang, 2023. "Does Environmental Regulation Promote the Infrastructure Investment Efficiency? Analysis Based on the Spatial Effects," IJERPH, MDPI, vol. 20(4), pages 1-24, February.
    6. Buchmayr, A. & Taelman, S.E. & Thomassen, G. & Verhofstadt, E. & Van Ootegem, L. & Dewulf, J., 2023. "A distance-to-sustainability-target approach for indicator aggregation and its application for the comparison of wind energy alternatives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).

    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:jsusta:v:15:y:2023:i:4:p:3692-:d:1071328. 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.