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dc.contributor.advisorPhan, Nguyen Ky Phuc
dc.contributor.authorVu, Minh Thuy
dc.date.accessioned2024-03-21T03:19:41Z
dc.date.available2024-03-21T03:19:41Z
dc.date.issued2022
dc.identifier.urihttp://keep.hcmiu.edu.vn:8080/handle/123456789/5099
dc.description.abstractSuppliers play a important role to make certain that goods are supplied continuously to the market for businesses. Businesses might not ensure a stable goods and products supply for the customers if they cannot keep a strong relationship with the suppliers. Failure to deliver items might cause the company's production and commercial operations to be delayed, resulting in customer loss. Furthermore, enhancing the company's production planning and scheduling is vital because of the number of manufacturing companies has expanded and everyday demand has increased. The main objective of this thesis is to solve problems of 2 phases in making confectionery products. In phase 1, this thesis proposes a multi-objective linear programming model to minimize the total purchasing and ordering cost when pruchasing materials for production to decrease the late-delivery materials from suppliers and the number of defective materials in supplier selection and order allocation with multi-item and multi supplier. In phase 2, this thesis also show an integer linear model for production scheduling in short-term to help Company T decrease tardy oder cost. This model allocate orders of customers in many due date and they are manufactured with limited capacity to minimize total cost for orders which are tardy. The working overtime periods are proposed which can complete received orders on time by determining the usage of each day of production. Then, addressing the needed minimum total completion time used to finish customer orders is compared to the planning horizon. CPLEX Interactive Optimizer program is applied to solve this problem to give the best result.en_US
dc.language.isoenen_US
dc.subjectOrder allocationen_US
dc.titleOrder Allocation Problem With Quantity Discount And Production Scheduling In Manufacturingen_US
dc.typeThesisen_US


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