IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2023i1p70-d1307235.html
   My bibliography  Save this article

Optimizing Inventory Management: A Comprehensive Analysis of Models Integrating Diverse Fuzzy Demand Functions

Author

Listed:
  • Mandeep Mittal

    (Department of Mathematics, School of Computer Science Engineering and Technology, Bennett University, Greater Noida 201310, India)

  • Vibhor Jain

    (Teerthankeer Mahaveer Institute of Management and Technology, Teerthanker Mahaveer University, Moradabad 244001, India)

  • Jayanti Tripathi Pandey

    (Department of Mathematics, Amity Institute of Applied Sciences, Amity University Uttar Pradesh, Noida 201301, India)

  • Muskan Jain

    (Department of Mathematics, Amity Institute of Applied Sciences, Amity University Uttar Pradesh, Noida 201301, India)

  • Himani Dem

    (Department of Mathematics, Ramjas College, University of Delhi, New Delhi 110007, India)

Abstract

This review study provides a comprehensive analysis of the classification of inventory models, with a focus on incorporating various fuzzy demand functions. The incorporation of fuzzy sets theory within inventory models is highlighted as a significant advancement in the field. The study emphasizes the importance of efficiently locating pertinent publications on this topic, rendering it a valuable resource for individuals interested in exploring inventory models that incorporate fuzzy demand functions. There was a need for a systematic and complete examination of recent breakthroughs in fuzzy inventory management. Our objective was to provide an illuminating overview of the significant developments in this field and offer insights into the probable future directions of research. Our evaluation of various model components has unveiled new and underexplored territories that may warrant further exploration. Perhaps it would be prudent to consider the possibility of establishing simpler models or incorporating qualitative methods into existing models and initiating a discourse on this topic.

Suggested Citation

  • Mandeep Mittal & Vibhor Jain & Jayanti Tripathi Pandey & Muskan Jain & Himani Dem, 2023. "Optimizing Inventory Management: A Comprehensive Analysis of Models Integrating Diverse Fuzzy Demand Functions," Mathematics, MDPI, vol. 12(1), pages 1-18, December.
    • Handle: RePEc:gam:jmathe:v:12:y:2023:i:1:p:70-:d:1307235
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/1/70/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/1/70/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    2. Neelanjana Rajput & R.K. Pandey & Anand Chauhan, 2022. "Fuzzy optimisation of a production model with CNTFN demand rate under trade-credit policy," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 21(2), pages 200-220.
    3. Janssen, Larissa & Claus, Thorsten & Sauer, Jürgen, 2016. "Literature review of deteriorating inventory models by key topics from 2012 to 2015," International Journal of Production Economics, Elsevier, vol. 182(C), pages 86-112.
    4. Wong, Bo K. & Lai, Vincent S., 2011. "A survey of the application of fuzzy set theory in production and operations management: 1998-2009," International Journal of Production Economics, Elsevier, vol. 129(1), pages 157-168, January.
    5. Salameh, M. K. & Jaber, M. Y., 2000. "Economic production quantity model for items with imperfect quality," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 59-64, March.
    6. Klein Haneveld, Willem K. & Teunter, Ruud H., 1998. "Effects of discounting and demand rate variability on the EOQ," International Journal of Production Economics, Elsevier, vol. 54(2), pages 173-192, January.
    7. Roy, Arindam & kar, Samarjit & Maiti, Manoranjan, 2010. "A volume flexible production-policy for randomly deteriorating item with trended demand and shortages," International Journal of Production Economics, Elsevier, vol. 128(1), pages 188-199, November.
    8. Bakker, Monique & Riezebos, Jan & Teunter, Ruud H., 2012. "Review of inventory systems with deterioration since 2001," European Journal of Operational Research, Elsevier, vol. 221(2), pages 275-284.
    9. Mula, J. & Poler, R. & Garcia-Sabater, J.P. & Lario, F.C., 2006. "Models for production planning under uncertainty: A review," International Journal of Production Economics, Elsevier, vol. 103(1), pages 271-285, September.
    10. Chakrabortty, Susovan & Pal, Madhumangal & Nayak, Prasun Kumar, 2013. "Intuitionistic fuzzy optimization technique for Pareto optimal solution of manufacturing inventory models with shortages," European Journal of Operational Research, Elsevier, vol. 228(2), pages 381-387.
    11. Neelanjana Rajput & Anand Chauhan & R.K. Pandey, 2022. "Optimisation of finite economic production quantity model under cloudy normalised triangular fuzzy number," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 43(1/2), pages 168-187.
    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. Osama Abdulaziz Alamri & Navneet Kumar Lamba & Mahesh Kumar Jayaswal & Mandeep Mittal, 2024. "A Sustainable Inventory Model with Advertisement Effort for Imperfect Quality Items under Learning in Fuzzy Monsoon Demand," Mathematics, MDPI, vol. 12(15), pages 1-41, August.
    2. Katherinne Salas-Navarro & Whady F. Florez & Leopoldo Eduardo Cárdenas-Barrón, 2024. "A vendor-managed inventory model for a three-layer supply chain considering exponential demand, imperfect system, and remanufacturing," Annals of Operations Research, Springer, vol. 332(1), pages 329-371, January.
    3. Manoranjan De & Barun Das & Manoranjan Maiti, 2016. "EPL models for complementary and substitute items under imperfect production process with promotional cost and selling price dependent demands," OPSEARCH, Springer;Operational Research Society of India, vol. 53(2), pages 259-277, June.
    4. David Opresnik & Maurizio Fiasché & Marco Taisch & Manuel Hirsch, 0. "An evolving fuzzy inference system for extraction of rule set for planning a product–service strategy," Information Technology and Management, Springer, vol. 0, pages 1-17.
    5. Alamri, Adel A. & Syntetos, Aris A., 2018. "Beyond LIFO and FIFO: Exploring an Allocation-In-Fraction-Out (AIFO) policy in a two-warehouse inventory model," International Journal of Production Economics, Elsevier, vol. 206(C), pages 33-45.
    6. Janssen, Larissa & Diabat, Ali & Sauer, Jürgen & Herrmann, Frank, 2018. "A stochastic micro-periodic age-based inventory replenishment policy for perishable goods," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 445-465.
    7. Roy, Arindam & kar, Samarjit & Maiti, Manoranjan, 2010. "A volume flexible production-policy for randomly deteriorating item with trended demand and shortages," International Journal of Production Economics, Elsevier, vol. 128(1), pages 188-199, November.
    8. Wenqiang Dai & Meng Zheng & Xu Chen & Zhuolin Yang, 0. "Online economic ordering problem for deteriorating items with limited price information," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-23.
    9. Haijema, René & Minner, Stefan, 2019. "Improved ordering of perishables: The value of stock-age information," International Journal of Production Economics, Elsevier, vol. 209(C), pages 316-324.
    10. Beullens, Patrick & Ghiami, Yousef, 2022. "Waste reduction in the supply chain of a deteriorating food item – Impact of supply structure on retailer performance," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1017-1034.
    11. Ghiami, Yousef & Demir, Emrah & Van Woensel, Tom & Christiansen, Marielle & Laporte, Gilbert, 2019. "A deteriorating inventory routing problem for an inland liquefied natural gas distribution network," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 45-67.
    12. Castellano, Davide & Glock, Christoph H., 2024. "Economic production quantity for a decaying item with stochastic demand and positive lead time," International Journal of Production Economics, Elsevier, vol. 267(C).
    13. N. Saranya & A. Shophia Lawrence, 2019. "A stochastic inventory system with replacement of perishable items," OPSEARCH, Springer;Operational Research Society of India, vol. 56(2), pages 563-582, June.
    14. Jui-Jung Liao & H. M. Srivastava & Shy-Der Lin, 2024. "Inventory models for non-instantaneous deteriorating items with expiration dates under the joined effect of preservation technology and linearly time-dependent holding cost when order-size linked to a," Annals of Operations Research, Springer, vol. 337(1), pages 197-233, June.
    15. Hasan Arslan & Seokjin Kim, 2025. "Managing perishable inventory when strategic customers form a reference on product availability," Annals of Operations Research, Springer, vol. 344(1), pages 47-78, January.
    16. Demeter, Krisztina & Szász, Levente & Kő, Andrea, 2019. "A text mining based overview of inventory research in the ISIR special issues 1994–2016," International Journal of Production Economics, Elsevier, vol. 209(C), pages 134-146.
    17. Cong Zheng & Quangui Pang & Tianpei Li & Guizheng Wang & Yiji Cai & Lei Yang, 2019. "The Farmers’ Channel Selection and Sustainable Analysis under Carbon Tax Policy," Sustainability, MDPI, vol. 11(10), pages 1-24, May.
    18. David Opresnik & Maurizio Fiasché & Marco Taisch & Manuel Hirsch, 2017. "An evolving fuzzy inference system for extraction of rule set for planning a product–service strategy," Information Technology and Management, Springer, vol. 18(2), pages 131-147, June.
    19. Ata Allah Taleizadeh & Sara Tavassoli & Arijit Bhattacharya, 2020. "Inventory ordering policies for mixed sale of products under inspection policy, multiple prepayment, partial trade credit, payments linked to order quantity and full backordering," Annals of Operations Research, Springer, vol. 287(1), pages 403-437, April.
    20. Kouki, Chaaben & Babai, M. Zied & Minner, Stefan, 2018. "On the benefit of dual-sourcing in managing perishable inventory," International Journal of Production Economics, Elsevier, vol. 204(C), pages 1-17.

    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:12:y:2023:i:1:p:70-:d:1307235. 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.