Collaborative Marketing and Procurement/Production Planning with Price-Dependent and Time-Varying Demand
Autor: | Liang-Tu Chen, 陳亮都 |
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Rok vydání: | 2005 |
Druh dokumentu: | 學位論文 ; thesis |
Popis: | 94 Although the evolving information management technologies provide a unified platform for managing and integrating core business processes within a firm, the decision-making between marketing and procurement/production planning remains loosely dependent. It is due in large part to the inherent weaknesses of the technologies such as fixed and static parameters settings and uncapacitated assumption. To remedy these drawbacks, we propose optimal decision models that solve the replenishment/production lot-size problem taking into account the dynamic aspects of customer’s demand. More specifically, we consider a single continuous decay product in a periodic review inventory system where shortages are allowed and fully backlogged. The demand of such product is assumed to be a multivariate function, depending solely on price and time. Unlike previous research, upward or downward adjustment of the selling price can be made at each review epoch. The objective of this research is to determine the periodic selling price and lot-size over multi-period planning horizon so that the total profit is maximized. The problems are formulated as dynamic programming models and solved by numerical search techniques. The models can be used as an add-on optimizer that coordinates distinct functions with the objective of maximizing total profit. Special emphasis is placed on the comparative study between the proposed optimization models that are based on the coordinated and decentralized policies, and the inventory followed by shortages (IFS) and shortages followed by inventory (SFI) replenishment/production systems. To even more understand the properties and behaviors of the proposed model and solution procedure, a real case study for sliced raw fishes at a local supermarket of a large national retail chain is carried out. |
Databáze: | Networked Digital Library of Theses & Dissertations |
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