IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v32y2021i6d10.1007_s10845-020-01633-7.html
   My bibliography  Save this article

A new Fuzzy C-Means and AHP-based three-phased approach for multiple criteria ABC inventory classification

Author

Listed:
  • Fatih Yiğit

    (Istanbul Arel University)

  • Şakir Esnaf

    (Istanbul University-Cerrahpaşa)

Abstract

ABC analysis is an efficient and easy-to-use methodology to classify inventory based on a single or multi-criteria basis that may consist of thousands of items. The first study by Dickie (Fact Manag Maint 109(7):92–94, 1951), based on a single criterion, is considered to be limited now. New studies focus on Multi-Criteria-Inventory Classification (MCIC) since such an extension of the criteria fits the realities of modern business decisions. The proposed approach in this study uses three-phased MCIC incorporating analytical hierarchy process (AHP), Fuzzy C-Means (FCM) algorithm, and a newly proposed Revised-Veto (Rveto) phase to meet the ABC classification principles and increase its applicability and flexibility. This new approach is called AHP–FCM–Rveto and proposed in this study for the first time. A numerical example taken from the literature is used to compare AHP–FCM–Rveto with other methods, and the results also show that the proposed methodology performs better. In the real-life example, the main advantage of compliance with the Pareto principle of the proposed method is shown.

Suggested Citation

  • Fatih Yiğit & Şakir Esnaf, 2021. "A new Fuzzy C-Means and AHP-based three-phased approach for multiple criteria ABC inventory classification," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1517-1528, August.
    • Handle: RePEc:spr:joinma:v:32:y:2021:i:6:d:10.1007_s10845-020-01633-7
    DOI: 10.1007/s10845-020-01633-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-020-01633-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10845-020-01633-7?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. Ng, Wan Lung, 2007. "A simple classifier for multiple criteria ABC analysis," European Journal of Operational Research, Elsevier, vol. 177(1), pages 344-353, February.
    2. Adrián Rodríguez Ramos & José M. Bernal de Lázaro & Alberto Prieto-Moreno & Antônio José Silva Neto & Orestes Llanes-Santiago, 2019. "An approach to robust fault diagnosis in mechanical systems using computational intelligence," Journal of Intelligent Manufacturing, Springer, vol. 30(4), pages 1601-1615, April.
    3. Zhou, Peng & Fan, Liwei, 2007. "A note on multi-criteria ABC inventory classification using weighted linear optimization," European Journal of Operational Research, Elsevier, vol. 182(3), pages 1488-1491, November.
    4. Jahangoshai Rezaee, Mustafa & Jozmaleki, Mehrdad & Valipour, Mahsa, 2018. "Integrating dynamic fuzzy C-means, data envelopment analysis and artificial neural network to online prediction performance of companies in stock exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 489(C), pages 78-93.
    5. R. J. Kuo & Y. S. Tseng & Zhen-Yao Chen, 2016. "Integration of fuzzy neural network and artificial immune system-based back-propagation neural network for sales forecasting using qualitative and quantitative data," Journal of Intelligent Manufacturing, Springer, vol. 27(6), pages 1191-1207, December.
    6. Mohammaditabar, Davood & Hassan Ghodsypour, Seyed & O'Brien, Chris, 2012. "Inventory control system design by integrating inventory classification and policy selection," International Journal of Production Economics, Elsevier, vol. 140(2), pages 655-659.
    7. Bottani, Eleonora & Rizzi, Antonio, 2008. "An adapted multi-criteria approach to suppliers and products selection--An application oriented to lead-time reduction," International Journal of Production Economics, Elsevier, vol. 111(2), pages 763-781, February.
    8. Lolli, F. & Ishizaka, A. & Gamberini, R., 2014. "New AHP-based approaches for multi-criteria inventory classification," International Journal of Production Economics, Elsevier, vol. 156(C), pages 62-74.
    9. Fan Liu & Ning Ma, 2019. "Multicriteria ABC Inventory Classification Using the Social Choice Theory," Sustainability, MDPI, vol. 12(1), pages 1-19, December.
    10. Altay Guvenir, H. & Erel, Erdal, 1998. "Multicriteria inventory classification using a genetic algorithm," European Journal of Operational Research, Elsevier, vol. 105(1), pages 29-37, February.
    11. Siamak Kheybari & S. Ali Naji & Fariba Mahdi Rezaie & Reza Salehpour, 2019. "ABC classification according to Pareto’s principle: a hybrid methodology," OPSEARCH, Springer;Operational Research Society of India, vol. 56(2), pages 539-562, June.
    12. Hongquan Jiang & Rongxi Wang & Zhiyong Gao & Jianmin Gao & Hongye Wang, 2019. "Classification of weld defects based on the analytical hierarchy process and Dempster–Shafer evidence theory," Journal of Intelligent Manufacturing, Springer, vol. 30(4), pages 2013-2024, April.
    13. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
    14. Seyedmohsen Hosseini & Abdullah Al Khaled, 2019. "A hybrid ensemble and AHP approach for resilient supplier selection," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 207-228, January.
    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. Lolli, F. & Ishizaka, A. & Gamberini, R., 2014. "New AHP-based approaches for multi-criteria inventory classification," International Journal of Production Economics, Elsevier, vol. 156(C), pages 62-74.
    2. Hu, Qiwei & Boylan, John E. & Chen, Huijing & Labib, Ashraf, 2018. "OR in spare parts management: A review," European Journal of Operational Research, Elsevier, vol. 266(2), pages 395-414.
    3. Hu, Qiwei & Chakhar, Salem & Siraj, Sajid & Labib, Ashraf, 2017. "Spare parts classification in industrial manufacturing using the dominance-based rough set approach," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1136-1163.
    4. Sheikh-Zadeh, Alireza & Rossetti, Manuel D. & Scott, Marc A., 2021. "Performance-based inventory classification methods for large-Scale multi-echelon replenishment systems," Omega, Elsevier, vol. 101(C).
    5. Zhang, Zeyu & Li, Kevin W. & Guo, Xiaolei & Huang, Jun, 2020. "A probability approach to multiple criteria ABC analysis with misclassification tolerance," International Journal of Production Economics, Elsevier, vol. 229(C).
    6. Liu, Jiapeng & Liao, Xiuwu & Zhao, Wenhong & Yang, Na, 2016. "A classification approach based on the outranking model for multiple criteria ABC analysis," Omega, Elsevier, vol. 61(C), pages 19-34.
    7. Hadhami Kaabi & Khaled Jabeur & Talel Ladhari, 2018. "A Genetic Algorithm-Based Classification Approach for Multicriteria ABC Analysis," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(06), pages 1805-1837, November.
    8. Ishizaka, Alessio & Lolli, Francesco & Balugani, Elia & Cavallieri, Rita & Gamberini, Rita, 2018. "DEASort: Assigning items with data envelopment analysis in ABC classes," International Journal of Production Economics, Elsevier, vol. 199(C), pages 7-15.
    9. Sheikh-Zadeh, Alireza & Rossetti, Manuel D., 2020. "Classification methods for problem size reduction in spare part provisioning," International Journal of Production Economics, Elsevier, vol. 219(C), pages 99-114.
    10. Siamak Kheybari & S. Ali Naji & Fariba Mahdi Rezaie & Reza Salehpour, 2019. "ABC classification according to Pareto’s principle: a hybrid methodology," OPSEARCH, Springer;Operational Research Society of India, vol. 56(2), pages 539-562, June.
    11. Subhadip Sarkar, 2023. "ABC classification using extended R-model, SVM and Lorenz curve," OPSEARCH, Springer;Operational Research Society of India, vol. 60(3), pages 1433-1455, September.
    12. Mohammaditabar, Davood & Hassan Ghodsypour, Seyed & O'Brien, Chris, 2012. "Inventory control system design by integrating inventory classification and policy selection," International Journal of Production Economics, Elsevier, vol. 140(2), pages 655-659.
    13. Hung-Lung Lin & Yu-Yu Ma, 2021. "A New Method of Storage Management Based on ABC Classification: A Case Study in Chinese Supermarkets’ Distribution Center," SAGE Open, , vol. 11(2), pages 21582440211, June.
    14. Millstein, Mitchell A. & Yang, Liu & Li, Haitao, 2014. "Optimizing ABC inventory grouping decisions," International Journal of Production Economics, Elsevier, vol. 148(C), pages 71-80.
    15. Sisi Wu & Yelin Fu & K. K. Lai & W. K. John Leung, 2018. "A Weighted Least-Square Dissimilarity Approach for Multiple Criteria ABC Inventory Classification," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(04), pages 1-12, August.
    16. Alessio Ishizaka & Maynard Gordon, 2017. "MACBETHSort: a multiple criteria decision aid procedure for sorting strategic products," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(1), pages 53-61, January.
    17. Feyzan Arikan & Senay Citak, 2017. "Multiple Criteria Inventory Classification in an Electronics Firm," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(02), pages 315-331, March.
    18. Kuei-Hu Chang & Yung-Chia Chang & Kai Chain & Hsiang-Yu Chung, 2016. "Integrating Soft Set Theory and Fuzzy Linguistic Model to Evaluate the Performance of Training Simulation Systems," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-29, September.
    19. Fan Liu & Ning Ma, 2019. "Multicriteria ABC Inventory Classification Using the Social Choice Theory," Sustainability, MDPI, vol. 12(1), pages 1-19, December.
    20. Ruzhdi Jashari, 2017. "Protection of Personal Data Requirement of Modern Times for the Functioning of the Security, Individual Freedoms and the Rule of Law," European Journal of Multidisciplinary Studies Articles, Revistia Research and Publishing, vol. 2, May Augus.

    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:spr:joinma:v:32:y:2021:i:6:d:10.1007_s10845-020-01633-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.