Dynamic Capacity Planning Under Multi-Products Stochastic Price-Demand Functions
Date Issued
2009
Date
2009
Author(s)
Li, Yi-Ling
Abstract
In our research, we focus on the industry capacity planning, using a multi-priced products dynamic capacity planning to solve it. The main difference between our model and traditional capacity planning is that we try to describe the impact caused by multi-priced products on capacity planning, emphasize the existence of distinct demand functions of different-priced products, and use Markov property to picture the stochastic demand environment faced by industries.n context we use dynamic planning to solve the best capacity increment quantities under different states, like different periods, capacity levels and demand environments. Exploit Microsoft Visual C# to help us calculate the iteration algorithm parts, and output the results to Microsoft Office Excel for analyses. In order to prove the rationality and feasibility of our model, we use ASP model (average selling price model) to be a comparison, so that we can compare their effects under multiple demand environment parameters. According to the results, we can observe the decision behaviors under variant parameters, and the difference between two models, so we can conclude that following the multi-price model decision policy can result better revenue than ASP model.
Subjects
Capacity planning
dynamic planning
multi-priced products
average selling price
Type
thesis
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