IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v74y2021ics0038012119302472.html
   My bibliography  Save this article

Relief demand forecasting based on intuitionistic fuzzy case-based reasoning

Author

Listed:
  • Shao, Jianfang
  • Liang, Changyong
  • Liu, Yujia
  • Xu, Jian
  • Zhao, Shuping

Abstract

Prediction for demand of relief materials is a fundamental condition of disaster relief operations, and the premise for optimal allocation of emergency resources. There are currently few research papers about demand forecasting at home and abroad. Looking at the characteristics of relief supply demand prediction with incomplete and inaccurate available information, and uncertainty of environment, we propose a demand prediction method called intuitionistic fuzzy case-based reasoning (IFCBR). This method combines the advantages of intuitionistic fuzzy theory and case-based reasoning (CBR). Also proposed in this paper are similarity calculation methods and a new weight calculation method. A case study is addressed to illustrate the prediction process of relief demand using the proposed method. Finally, the validity of the method is verified by an empirical evaluation experiment in which actual earthquake disaster cases are introduced. This forecasting method provides decision support for relief material requirements, and provides a basis for resource allocation.

Suggested Citation

  • Shao, Jianfang & Liang, Changyong & Liu, Yujia & Xu, Jian & Zhao, Shuping, 2021. "Relief demand forecasting based on intuitionistic fuzzy case-based reasoning," Socio-Economic Planning Sciences, Elsevier, vol. 74(C).
    • Handle: RePEc:eee:soceps:v:74:y:2021:i:c:s0038012119302472
    DOI: 10.1016/j.seps.2020.100932
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0038012119302472
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.seps.2020.100932?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. Mete, Huseyin Onur & Zabinsky, Zelda B., 2010. "Stochastic optimization of medical supply location and distribution in disaster management," International Journal of Production Economics, Elsevier, vol. 126(1), pages 76-84, July.
    2. Xiaoxin Zhu & Guanghai Zhang & Baiqing Sun, 2019. "A comprehensive literature review of the demand forecasting methods of emergency resources from the perspective of artificial intelligence," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 97(1), pages 65-82, May.
    3. Itzhak Gilboa & David Schmeidler, 1995. "Case-Based Decision Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(3), pages 605-639.
    4. Campbell, Ann Melissa & Jones, Philip C., 2011. "Prepositioning supplies in preparation for disasters," European Journal of Operational Research, Elsevier, vol. 209(2), pages 156-165, March.
    5. Sheu, Jiuh-Biing, 2007. "An emergency logistics distribution approach for quick response to urgent relief demand in disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 687-709, November.
    6. Davis, Lauren B. & Samanlioglu, Funda & Qu, Xiuli & Root, Sarah, 2013. "Inventory planning and coordination in disaster relief efforts," International Journal of Production Economics, Elsevier, vol. 141(2), pages 561-573.
    7. Sheu, Jiuh-Biing, 2010. "Dynamic relief-demand management for emergency logistics operations under large-scale disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(1), pages 1-17, January.
    8. Rawls, Carmen G. & Turnquist, Mark A., 2012. "Pre-positioning and dynamic delivery planning for short-term response following a natural disaster," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 46-54.
    9. Rawls, Carmen G. & Turnquist, Mark A., 2010. "Pre-positioning of emergency supplies for disaster response," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 521-534, May.
    10. Huang Xing & Zhou Zhonglin & Wang Shaoyu, 2015. "The prediction model of earthquake casuailty based on robust wavelet v-SVM," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(2), pages 717-732, June.
    11. Xihui Wang & Yunfei Wu & Liang Liang & Zhimin Huang, 2016. "Service outsourcing and disaster response methods in a relief supply chain," Annals of Operations Research, Springer, vol. 240(2), pages 471-487, May.
    12. J.H. Ruan & X.P. Wang & F.T.S. Chan & Y. Shi, 2016. "Optimizing the intermodal transportation of emergency medical supplies using balanced fuzzy clustering," International Journal of Production Research, Taylor & Francis Journals, vol. 54(14), pages 4368-4386, July.
    13. Meimei Zheng & Yan Shu & Kan Wu, 2015. "On optimal emergency orders with updated demand forecast and limited supply," International Journal of Production Research, Taylor & Francis Journals, vol. 53(12), pages 3692-3719, June.
    14. Yi, Wei & Kumar, Arun, 2007. "Ant colony optimization for disaster relief operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 660-672, November.
    15. Das, Rubel & Hanaoka, Shinya, 2014. "Relief inventory modelling with stochastic lead-time and demand," European Journal of Operational Research, Elsevier, vol. 235(3), pages 616-623.
    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. Andrea Kolková & Aleksandr Kljuènikov, 2021. "Demand forecasting: an alternative approach based on technical indicator Pbands," Oeconomia Copernicana, Institute of Economic Research, vol. 12(4), pages 1063-1094, December.
    2. Sara Rye & Emel Aktas, 2023. "A Rule-Based Predictive Model for Estimating Human Impact Data in Natural Onset Disasters—The Case of a PRED Model," Logistics, MDPI, vol. 7(2), pages 1-24, May.
    3. Fei, Liguo & Wang, Yanqing, 2022. "Demand prediction of emergency materials using case-based reasoning extended by the Dempster-Shafer theory," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).

    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. A. Anaya-Arenas & J. Renaud & A. Ruiz, 2014. "Relief distribution networks: a systematic review," Annals of Operations Research, Springer, vol. 223(1), pages 53-79, December.
    2. Renata Turkeš & Daniel Palhazi Cuervo & Kenneth Sörensen, 2019. "Pre-positioning of emergency supplies: does putting a price on human life help to save lives?," Annals of Operations Research, Springer, vol. 283(1), pages 865-895, December.
    3. Yusen Ye & Wen Jiao & Hong Yan, 2020. "Managing Relief Inventories Responding to Natural Disasters: Gaps Between Practice and Literature," Production and Operations Management, Production and Operations Management Society, vol. 29(4), pages 807-832, April.
    4. Abhishek Behl & Pankaj Dutta, 2019. "Humanitarian supply chain management: a thematic literature review and future directions of research," Annals of Operations Research, Springer, vol. 283(1), pages 1001-1044, December.
    5. Li, Xiaoping & Batta, Rajan & Kwon, Changhyun, 2017. "Effective and equitable supply of gasoline to impacted areas in the aftermath of a natural disaster," Socio-Economic Planning Sciences, Elsevier, vol. 57(C), pages 25-34.
    6. Jiang-Hua Zhang & Xiao-Qing Sun & Rui Zhu & Ming Li & Wang Miao, 2017. "Solving an emergency rescue materials problem under the joint reserves mode of government and framework agreement suppliers," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-20, October.
    7. Meng, Qingchun & Kao, Zhiping & Guo, Ying & Bao, Chunbing, 2023. "An emergency supplies procurement strategy based on a bidirectional option contract," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    8. Loree, Nick & Aros-Vera, Felipe, 2018. "Points of distribution location and inventory management model for Post-Disaster Humanitarian Logistics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 1-24.
    9. Rezaei-Malek, Mohammad & Tavakkoli-Moghaddam, Reza & Cheikhrouhou, Naoufel & Taheri-Moghaddam, Alireza, 2016. "An approximation approach to a trade-off among efficiency, efficacy, and balance for relief pre-positioning in disaster management," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 485-509.
    10. Rivera-Royero, Daniel & Galindo, Gina & Yie-Pinedo, Ruben, 2020. "Planning the delivery of relief supplies upon the occurrence of a natural disaster while considering the assembly process of the relief kits," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    11. Aghajani, Mojtaba & Ali Torabi, S. & Altay, Nezih, 2023. "Resilient relief supply planning using an integrated procurement-warehousing model under supply disruption," Omega, Elsevier, vol. 118(C).
    12. Wang, Jing & Cai, Jianping & Yue, Xiaohang & Suresh, Nallan C., 2021. "Pre-positioning and real-time disaster response operations: Optimization with mobile phone location data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
    13. Cailin Wang & Jidong Wu & Xin He & Mengqi Ye & Wenhui Liu & Rumei Tang, 2018. "Emerging Trends and New Developments in Disaster Research after the 2008 Wenchuan Earthquake," IJERPH, MDPI, vol. 16(1), pages 1-19, December.
    14. Lu, Chung-Cheng & Ying, Kuo-Ching & Chen, Hui-Ju, 2016. "Real-time relief distribution in the aftermath of disasters – A rolling horizon approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 1-20.
    15. Wilson, Duncan T. & Hawe, Glenn I. & Coates, Graham & Crouch, Roger S., 2013. "A multi-objective combinatorial model of casualty processing in major incident response," European Journal of Operational Research, Elsevier, vol. 230(3), pages 643-655.
    16. Fei, Liguo & Wang, Yanqing, 2022. "Demand prediction of emergency materials using case-based reasoning extended by the Dempster-Shafer theory," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    17. Alem, Douglas & Clark, Alistair & Moreno, Alfredo, 2016. "Stochastic network models for logistics planning in disaster relief," European Journal of Operational Research, Elsevier, vol. 255(1), pages 187-206.
    18. Paul, Jomon A. & Zhang, Minjiao, 2019. "Supply location and transportation planning for hurricanes: A two-stage stochastic programming framework," European Journal of Operational Research, Elsevier, vol. 274(1), pages 108-125.
    19. Rennemo, Sigrid Johansen & Rø, Kristina Fougner & Hvattum, Lars Magnus & Tirado, Gregorio, 2014. "A three-stage stochastic facility routing model for disaster response planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 116-135.
    20. Masoud Mahootchi & Sajjad Golmohammadi, 2018. "Developing a new stochastic model considering bi-directional relations in a natural disaster: a possible earthquake in Tehran (the Capital of Islamic Republic of Iran)," Annals of Operations Research, Springer, vol. 269(1), pages 439-473, October.

    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:soceps:v:74:y:2021:i:c:s0038012119302472. 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/seps .

    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.