IDEAS home Printed from https://ideas.repec.org/a/spr/snopef/v4y2023i3d10.1007_s43069-023-00237-0.html
   My bibliography  Save this article

Novel Methods for Solving Multi-Objective Non-linear Inventory Model of Highly Deteriorating Items

Author

Listed:
  • Minakshi Panda

    (Siksha ’O’Anusandhan Deemed to be University)

  • Anuradha Sahoo

    (Siksha ’O’Anusandhan Deemed to be University)

Abstract

In this study, multi-objective inventory model of deteriorating and perishable items is developed under space and budget constraints. Demand is stock dependent and power function of time. This model is completely a new model in the sense that the model is applied to those items whose deterioration rate is maximum. Shortages are allowed in each cycle. The main aim of this paper is to find different time points for each cycle where shortage occurs and inventory depletes, respectively, so that both total cost and shortage cost can be minimized simultaneously. The model is developed in both crisp and fuzzy environment. In fuzzy environment, the objectives are considered as fuzzy constraints. For this, the decision maker needs to establish an aspiration level for the objective functions which he wants to achieve as far as possible. This paper aims to use fuzzy non-linear programming (FNLP) and intuitionistic fuzzy optimization (IFO) techniques for the multi-objective inventory model. Comparison is based on different optimization techniques in different environment using numerical examples. A graph of the objective functions is provided. A system diagram of the model and an algorithm for solving the model are provided. Also, sensitivity analysis is made using different parameters of the model.

Suggested Citation

  • Minakshi Panda & Anuradha Sahoo, 2023. "Novel Methods for Solving Multi-Objective Non-linear Inventory Model of Highly Deteriorating Items," SN Operations Research Forum, Springer, vol. 4(3), pages 1-22, September.
  • Handle: RePEc:spr:snopef:v:4:y:2023:i:3:d:10.1007_s43069-023-00237-0
    DOI: 10.1007/s43069-023-00237-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s43069-023-00237-0
    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/s43069-023-00237-0?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. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    2. Hwang, Hark & Hahn, Kyu Hun, 2000. "An optimal procurement policy for items with an inventory level-dependent demand rate and fixed lifetime," European Journal of Operational Research, Elsevier, vol. 127(3), pages 537-545, December.
    3. Joaquín Sicilia & Jaime Febles-Acosta & Manuel González-De La Rosa, 2012. "Deterministic Inventory Systems With Power Demand Pattern," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 29(05), pages 1-28.
    4. S. Banerjee & T. K. Roy, 2010. "Solution of Single and Multiobjective Stochastic Inventory Models with Fuzzy Cost Components by Intuitionistic Fuzzy Optimization Technique," Advances in Operations Research, Hindawi, vol. 2010, pages 1-19, June.
    5. Chakrabarti, T. & Chaudhuri, K. S., 1997. "An EOQ model for deteriorating items with a linear trend in demand and shortages in all cycles," International Journal of Production Economics, Elsevier, vol. 49(3), pages 205-213, May.
    6. Yang, Chih-Te, 2014. "An inventory model with both stock-dependent demand rate and stock-dependent holding cost rate," International Journal of Production Economics, Elsevier, vol. 155(C), pages 214-221.
    7. Joaquín Sicilia & Jaime Febles-Acosta & Manuel González-De la Rosa, 2013. "Economic order quantity for a power demand pattern system with deteriorating items," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 7(5), pages 577-593.
    8. Giri, B. C. & Pal, S. & Goswami, A. & Chaudhuri, K. S., 1996. "An inventory model for deteriorating items with stock-dependent demand rate," European Journal of Operational Research, Elsevier, vol. 95(3), pages 604-610, December.
    9. Pando, Valentín & San-José, Luis A. & García-Laguna, Juan & Sicilia, Joaquín, 2013. "An economic lot-size model with non-linear holding cost hinging on time and quantity," International Journal of Production Economics, Elsevier, vol. 145(1), pages 294-303.
    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. Sicilia, Joaquín & González-De-la-Rosa, Manuel & Febles-Acosta, Jaime & Alcaide-López-de-Pablo, David, 2014. "Optimal policy for an inventory system with power demand, backlogged shortages and production rate proportional to demand rate," International Journal of Production Economics, Elsevier, vol. 155(C), pages 163-171.
    2. Irfan Ali & Srikant Gupta & Aquil Ahmed, 2019. "Multi-objective linear fractional inventory problem under intuitionistic fuzzy environment," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(2), pages 173-189, April.
    3. Yang, Chih-Te, 2014. "An inventory model with both stock-dependent demand rate and stock-dependent holding cost rate," International Journal of Production Economics, Elsevier, vol. 155(C), pages 214-221.
    4. Valentín Pando & Luis A. San-José & Joaquín Sicilia, 2021. "An Inventory Model with Stock-Dependent Demand Rate and Maximization of the Return on Investment," Mathematics, MDPI, vol. 9(8), pages 1-18, April.
    5. Sicilia, Joaquín & González-De-la-Rosa, Manuel & Febles-Acosta, Jaime & Alcaide-López-de-Pablo, David, 2014. "An inventory model for deteriorating items with shortages and time-varying demand," International Journal of Production Economics, Elsevier, vol. 155(C), pages 155-162.
    6. Ajoy Hatibaruah & Sumit Saha, 2023. "An inventory model for two-parameter Weibull distributed ameliorating and deteriorating items with stock and advertisement frequency dependent demand under trade credit and preservation technology," OPSEARCH, Springer;Operational Research Society of India, vol. 60(2), pages 951-1002, June.
    7. Zhou, Yong-Wu & Min, Jie & Goyal, Suresh K., 2008. "Supply-chain coordination under an inventory-level-dependent demand rate," International Journal of Production Economics, Elsevier, vol. 113(2), pages 518-527, June.
    8. Luis A. San-José & Joaquín Sicilia & Manuel González-de-la-Rosa & Jaime Febles-Acosta, 2021. "Optimal Price and Lot Size for an EOQ Model with Full Backordering under Power Price and Time Dependent Demand," Mathematics, MDPI, vol. 9(16), pages 1-16, August.
    9. Urban, Timothy L., 2005. "Inventory models with inventory-level-dependent demand: A comprehensive review and unifying theory," European Journal of Operational Research, Elsevier, vol. 162(3), pages 792-804, May.
    10. San-José, L.A. & Sicilia, J. & García-Laguna, J., 2015. "Analysis of an EOQ inventory model with partial backordering and non-linear unit holding cost," Omega, Elsevier, vol. 54(C), pages 147-157.
    11. Sudarshan Bardhan & Haimanti Pal & Bibhas Chandra Giri, 2019. "Optimal replenishment policy and preservation technology investment for a non-instantaneous deteriorating item with stock-dependent demand," Operational Research, Springer, vol. 19(2), pages 347-368, June.
    12. Luis A. San-José & Joaquín Sicilia & Manuel González-De-la-Rosa & Jaime Febles-Acosta, 2020. "Best pricing and optimal policy for an inventory system under time-and-price-dependent demand and backordering," Annals of Operations Research, Springer, vol. 286(1), pages 351-369, March.
    13. Vuciterna, Rina & Thomsen, Michael & Popp, Jennie & Musliu, Arben, 2017. "Efficiency and Competitiveness of Kosovo Raspberry Producers," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252770, Southern Agricultural Economics Association.
    14. Berna Tektas Sivrikaya & Ferhan Cebi & Hasan Hüseyin Turan & Nihat Kasap & Dursun Delen, 2017. "A fuzzy long-term investment planning model for a GenCo in a hybrid electricity market considering climate change impacts," Information Systems Frontiers, Springer, vol. 19(5), pages 975-991, October.
    15. Collan, Mikael, 2008. "New Method for Real Option Valuation Using Fuzzy Numbers," Working Papers 466, IAMSR, Åbo Akademi.
    16. Kim, Jong Soon & Whang, Kyu-Seung, 1998. "A tolerance approach to the fuzzy goal programming problems with unbalanced triangular membership function," European Journal of Operational Research, Elsevier, vol. 107(3), pages 614-624, June.
    17. Berna Tektaş & Hasan Hüseyin Turan & Nihat Kasap & Ferhan Çebi & Dursun Delen, 2022. "A Fuzzy Prescriptive Analytics Approach to Power Generation Capacity Planning," Energies, MDPI, vol. 15(9), pages 1-26, April.
    18. Jaggi, Chandra K. & Aggarwal, K.K. & Goel, S.K., 2006. "Optimal order policy for deteriorating items with inflation induced demand," International Journal of Production Economics, Elsevier, vol. 103(2), pages 707-714, October.
    19. Chen, Lisa Y. & Wang, Tien-Chin, 2009. "Optimizing partners' choice in IS/IT outsourcing projects: The strategic decision of fuzzy VIKOR," International Journal of Production Economics, Elsevier, vol. 120(1), pages 233-242, July.
    20. Víctor G. Alfaro-García & Anna M. Gil-Lafuente & Gerardo G. Alfaro Calderón, 2017. "A fuzzy approach to a municipality grouping model towards creation of synergies," Computational and Mathematical Organization Theory, Springer, vol. 23(3), pages 391-408, September.

    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:snopef:v:4:y:2023:i:3:d:10.1007_s43069-023-00237-0. 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.