Dynamic Capacity Planning in a Multi-Product Supply Chain under Price Differentiation
Date Issued
2010
Date
2010
Author(s)
Liu, Ya-Ling
Abstract
In this research, we present a dynamic programming approach to capacity planning under demand uncertainty. Demand is dependent on time and price. We define 3 demand scenarios which are formulated as linear functions and describe them with Markov property. We can have a series of capacity expansion policy which the long term profit is maximized subjected to floor space and budget constraint.
We focus on the impact of multi-price model in an industry which has several process stages and produce multiple products. In order to prove the robust of our model, we compare it to ASP (Average Selling Price) model. And the result shows that multi-price model always has better performance in profit than ASP model.
Subjects
Dynamic Programming
Capacity Planning
Average Selling Price
Multiple Price
Supply Chain
Type
thesis
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