Summary: The concept of robust design was first introduced by Genuchi Taguchi in the 1960s, and was subsequently accepted in the field of experimental design and quality control. The basic idea of robust design is to make a manufacturing process insensitive to noise factors. Taguchi divided variables into two categories: design factors and noise factors. Design factors are controllable decisions affecting a process. Noise factors are those variables representing field sources of variation. The goal is to design a product or process to be robust to noise. One way to determine a robust design is to find a set of design variables that provides the minimum deviation from a target value of the response when noise variables are considered at different levels. We propose that a similar idea can be applied to the design of supply chains, namely robust supply chain design. Supply chain design models determine strategic decisions, such as the most cost-effective location of facilities (including plants and distribution centers), flow of goods, services, information and funds throughout the supply chain, and assignment of customers to distribution centers. We next briefly and selectively review deterministic analytical models and stochastic analytical models for strategic supply chain design.