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    Study on inventory control under uncertainty in supply chain processes

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    Date
    2024
    Author
    Praveen, V P
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    Abstract
    Inventory control and supply chain processes are essential components in efficiently managing the flow of goods and materials within a business. Effective inventory man- agement aims to strike a balance, avoiding overstock and stock shortages while ensur- ing sufficient inventory to support smooth organizational operations. In supply chain processes, coordination between suppliers, manufacturers, and distributors is vital in meeting customer demand while maintaining operational efficiency. This research fo- cuses on various inventory control and supply chain management models, addressing critical aspects like deterioration, demand fluctuations, and financing strategies. The study explores by proposing a model for inventory control for items with a general de- terioration rate, emphasizing the optimization of costs over time. To provide insights into balancing profitability and credit terms, the research develops an EOQ (Economic Order Quantity) model for deteriorating items, factoring in two-level trade credit fi- nancing with expiration dates. The study investigates inventory decisions for items experiencing both deterioration and amelioration, incorporating partial backlogging and time-varying demand. The research examines an integrated supply chain model with manufacturer and retailer where product demand is influenced by factors like price, freshness, and advertisement strategies, allowing for more adaptive approaches in highly competitive markets. Finally, the study concludes with a summary of find- ings and outlines future research directions, particularly in extending these models to address emerging challenges in global supply chains. This research also includes numer- ical examples and sensitivity analysis to validate and illustrate the proposed models. Through these analyses, we aim to demonstrate the practical applicability and effec- tiveness of the models in addressing real-world inventory and supply chain challenges.
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    https://hdl.handle.net/20.500.12818/2668
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    • Doctoral Theses [19]

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