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dc.contributor.advisorHo, Thi Thu Hoa
dc.contributor.authorTran, Nhat Nam
dc.date.accessioned2025-02-12T07:16:09Z
dc.date.available2025-02-12T07:16:09Z
dc.date.issued2024-08
dc.identifier.urihttp://keep.hcmiu.edu.vn:8080/handle/123456789/6482
dc.description.abstractThis research presents an integrated inventory optimization approach for a company managing diverse product categories, proposing three distinct optimization models tailored to specific product groups: FLUKE, Group A, and Group B. The study employs a range of inventory optimization techniques to address the unique characteristics of each group. For the FLUKE group, a periodic review inventory optimization model is developed, incorporating inventory balance constraints and safety stock considerations to determine optimal order quantities and inventory levels. Group A utilizes a multi-item deterministic inventory optimization framework, integrating an (s,S) inventory policy optimization and price adjustment factor optimization to minimize total inventory costs while accounting for deterministic demand. The model for Group B employs a multi-item deterministic inventory optimization approach, encompassing (s,S) policy optimization, backorder optimization, and capacity constraints to determine optimal reorder points, order-up-to levels, order quantities, and backorder levels. Additionally, a multi-item stochastic inventory optimization model is developed for Group C, integrating cycle service level optimization, lead time distribution modeling, order quantity optimization, and capacity constraints. This model aims to optimize order decisions, quantities, inventory levels, and backorder levels while minimizing costs and achieving prescribed cycle service levels, accounting for stochastic lead times. The methodology leverages mathematical programming techniques and constraint programming to formulate and solve the optimization problems, considering a comprehensive set of decision variables and constraints. The objective functions aim to minimize total inventory costs, including holding, ordering, backorder, and penalty costs, subject to various constraints such as inventory balance equations, service level requirements, capacity restrictions, lead time considerations, and non-negativity conditions. By developing a comprehensive framework that addresses the complexities of multi-item inventory management across different product categories, this research contributes significantly to the field of inventory optimization. The proposed models offer practical guidance for organizations seeking to enhance operational efficiency, achieve cost savings, and maximize profitability through improved inventory control strategies. This integrated approach demonstrates the potential for tailored optimization techniques to address the diverse challenges faced in modern supply chain management.en_US
dc.language.isoenen_US
dc.subjectMulti-model inventory optimizationen_US
dc.subjectproduct lossen_US
dc.titleIntegrated Inventory Optimization: A Case Study Of Anh Phat Trading Manufacture Co., Ltden_US
dc.typeThesisen_US


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