Sourcing with random yields and stochastic demand: A newsvendor approach

• Published in: Computers & operations research Vol. 34; no. 12; pp. 3682 - 3690
• Main Authors: Yang, Shitao, Yang, Jian, Abdel-Malek, Layek
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 01.12.2007; Pergamon Press Inc
• Subjects: Demand; Newsvendor; Non-linear programming; Problem solving; Profit maximization; Sourcing; Stochastic models; Studies; Supplier selection; Supply chain; Supply chain; Supplier selection; Newsvendor; Non-linear programming
• ISSN: 0305-0548; 1873-765X; 0305-0548
• DOI: 10.1016/j.cor.2006.01.015

We studied a supplier selection problem, where a buyer, while facing random demand, is to decide ordering quantities from a set of suppliers with different yields and prices. We provided the mathematical formulation for the buyer's profit maximization problem and proposed a solution method based on a combination of the active set method and the Newton search procedure. Our computational study shows that the proposed method can solve the problem efficiently, and is able to generate interesting and insightful results that lead us to various managerial implications. In today's globally competitive environment, decision makers in supply chains face numerous challenges particularly regarding the selection of suppliers or outsourcing partners. To assist in this endeavor, we examined a double-layered supply chain where a buyer facing the end users has the option of selecting among a cohort of suppliers. The available suppliers may have different yield rates and unit costs. The buyer has to decide, given the stochastic nature of the problem's governing parameters, whether or not to order from each supplier, and if so how much. We developed a ‘newsvendor-style’ model for the problem, and proposed a solution algorithm for it. Numerical studies were performed to provide some insights for supplier selection and order quantity decisions.