Volume 56, Number 1, January-February 2022
|Page(s)||475 - 500|
|Published online||04 March 2022|
Inventory decision for products with deterioration and expiration dates for pollution-based supply chain model in fuzzy environments
Department of Mathematics, Sidho-Kanho-Birsha University, Purulia 723104, West Bengal, India
2 Department of Mathematics, Midnapore College (Autonomous), Paschim Medinipur 721101, West Bengal, India
Accepted: 5 February 2022
The proposed study addresses a two-echelon sustainable supply chain (SC) model with a single-vendor and a single-buyer by considering the detrimental impacts of environmental pollution due to production. Moreover, an estimation function of pollution measure due to production is developed through a separate modelling. In the entire supply chain, we assume the deterioration rate increases with time and it also depends on the product’s expiration date. On the other hand, the demand for deteriorating items at the buyer’s end is assumed to be the dense fuzzy number because of learning effect. The model is developed by defining the exact profit functions for the vendor, the buyer and the entire supply chain and solved by classical method. These lead to the determination of individual optimal policies, as well as the optimal policy for the joint integrated supply chain. Fuzzifying the final objective function via dense fuzzy rule, we have employed extended ranking procedure for its defuzzification. A comparative study on numerical illustration of the proposed objective function under centralized and decentralized policies in both crisp and dense fuzzy environment has also been studied to validate the model. Finally graphical illustrations and sensitivity analysis have been made for its global justifications.
Mathematics Subject Classification: 90B05
Key words: Supply chain / inventory / expiry date / dense fuzzy set / learning effect
© The authors. Published by EDP Sciences, ROADEF, SMAI 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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