An Inventory Model for Perishable Goods with Demand that Varies Probabilistically with Selling Price Using a Pentagonal Fuzzy Framework

Ashish Negi (), Ompal Singh (), Ajay Singh Yadav () and Krishan Kumar Yadav ()
Additional contact information
Ashish Negi: SRM Institute of Science and Technology, Delhi-NCR Campus
Ompal Singh: SRM Institute of Science and Technology, Delhi-NCR Campus
Ajay Singh Yadav: SRM Institute of Science and Technology, Delhi-NCR Campus
Krishan Kumar Yadav: JECRC University

SN Operations Research Forum, 2025, vol. 6, issue 4, 1-28

Abstract: Abstract Managing inventory for perishable goods in industries such as food processing and pharmaceuticals poses significant challenges due to the uncertain nature of demand, which is often influenced by factors such as price, timing, and product shelf life. Pentagonal Fuzzy Numbers (PFNs) provide a more realistic representation of expert judgment by considering five distinct evaluation points, thereby enhancing the accuracy and flexibility of uncertainty modeling in production inventory systems. To address these complexities, this study proposes an analytical inventory model formulated within a pentagonal fuzzy framework in place of triangular or trapezoidal fuzzy numbers. The model effectively handles deteriorating items considering a probabilistic demand rate function and applying two defuzzification techniques: Graded Mean Integration Representation (GMIR) and Signed Distance (SD). The primary objective of the model is to maximize total average profit function by simultaneously optimizing the cycle length and selling price. Analytical optimization is carried out using MATLAB software (version R2021b), supported by detailed numerical examples for all three cases and a sensitivity analysis conducted under both crisp and fuzzy environments. This analysis highlights the influence of key system parameters on model performance. Additionally, the graphical results are presented in a simplified and focused format to effectively illustrate the optimal outcomes derived from the model.

Keywords: Perishable inventory model; Production; Probabilistic price dependent demand; Pentagonal fuzzy number; GMIR-SDM; Analytical optimization method (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s43069-025-00555-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:snopef:v:6:y:2025:i:4:d:10.1007_s43069-025-00555-5

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/43069

DOI: 10.1007/s43069-025-00555-5

Access Statistics for this article

SN Operations Research Forum is currently edited by Marco Lübbecke

More articles in SN Operations Research Forum from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().