A Neutrosophic Approach to Inventory Modelling under Uncertain Demand

Inventory management plays an important role in ensuring the
efficient flow of goods while maintaining a balance between supplyand demand. Most classical inventory models assume that
parameters such as demand, ordering cost, and holding cost areknown precisely. In real-world situations, however, these parametersare often subject to uncertainty and incomplete information due tofluctuating market conditions and estimation errors. As a result,deterministic models may not always capture the complexity ofpractical inventory systems.To address this limitation, the present chapter explores an inventorymodelling approach based onneutrosophic theory. Neutrosophicrepresentation allows uncertainty to be expressed through threeindependent components: truth,indeterminacy, and falsity. Thisframework provides greater flexibility for modelling situations where information is not completely certain or may contain indeterminate
elements.
In the proposed model, demand is represented in a neutrosophic form
while the cost structure follows the conventional inventory framework
consisting of ordering and holding costs. A neutrosophic total cost
function is formulated and analysed to determine the inventory policy
that minimizes the overall cost of the system. The mathematical
formulation is supported with a numerical example to demonstrate
the practical applicability of the model.
A comparison with the classical deterministic inventory model is also
presented to highlight the effect of incorporating neutrosophic
parameters. The analysis shows that the neutrosophic approachprovides a broader representation of uncertainty while retaining theinterpretability of traditional inventory models. The study illustrateshow neutrosophic theory can be effectively applied to inventorydecision-making problems involving indeterminate information.
Keywords: Neutrosophic set; Inventory management; Inventory model;Uncertainty modeling; Total inventory cost; Optimization.