SUPPLY CHAIN MANAGEMENT: PRICING, PRODUCTION, AND ALLOCATION

Abstract

With the globalization, the development of e-commence, and the availability of data, efficient and effective supply chain management becomes essential. In this thesis, we first evaluate the supply chain performance when the retailer is target-oriented---his objective is to maximize the ability to achieve profit target. We then consider a multi-product Newsvendor problem and a joint pricing and production problem for the producer/retailer in a supply chain. We model each problem as a robust model and use K-means clustering to construct the corresponding ambiguity set. The two robust models are further reformulated into (mixed integer) linear programing. The implementation of the solutions from our proposed framework on a real dataset yields surprisingly good performance in the out-of-sample test. In the last part of the thesis, we compare two well-known allocation rules: average cost pricing and the Shapley value, respectively, in the cost sharing problem, in which multiple retailers are jointly involved in an activity and need to share the aggregate profit or cost.