**一、讲座题目：**

Robust Dynamic Pricing with Two Substitutable Products

**二、讲座时间：**

2020年6月30日上午9:00

**三、讲座地点**

Zoom ID: 968 754 8121

**四、主讲人**

美国马里兰大学Smith商学院陈志龙教授

**五、讲座摘要**

We consider a dynamic pricing problem with two substitutable products involving a number of business rules commonly seen in practice. Demand substitution exists between the two products in each period (called inter-product substitution), and may also exist across different time periods (called intertemporal substitution). However, there is limited demand information such that the underlying probability distributions of the demand cannot be characterized precisely. We use an interval to represent, respectively, the demand of each individual product in each period, the aggregate demand of the two products in each period, and the total aggregate demand of the two products across multiple time periods. We propose a robust optimization model for this problem to maximize the worst-case total revenue. For the problem with inter-product demand substitution only, we develop a dynamic programming algorithm and show that the search spaces in the DP can be reduced greatly, which enables the algorithm to generate optimal solutions in a reasonable amount of time. For the problem with both inter-product and intertemporal demand substitutions, we develop a more complex dynamic programming algorithm and design a fully polynomial-time approximation scheme which guarantees a proven near optimal solution in a manageable computational time for practically sized problems. For a special case of this problem where one product always has a higher demand uncertainty than the other product, we show that the search spaces in the DP can be reduced greatly in a way similar to the DP for the problem with inter-product demand substitution only. Our computational results show that compared to a risk neutral approach, our robust optimization approach can decrease the variance of the revenue at a small expense of the average revenue. We also generate a number of managerial insights: (i) None of the key structural properties commonly studied in the pricing literature hold for our problem, (ii) The revenue impact of under/over-estimating the lower and upper bounds of the demand intervals is generally insignificant, and (iii) The revenue impact of ignoring intertemporal demand substitution when such substitution exists can be quite significant.

**六、主讲人简介**

Dr. Zhi-Long Chen received his PhD degree in Operations Research from Princeton University in 1997. He is currently Orkand Corporation Professor of Management Science at the Robert H. Smith School of Business, University of Maryland. His research interests cover supply chain scheduling, dynamic pricing, transportation and logistics operations, and optimization. Dr. Chen has conducted several National Science Foundation funded research projects in these areas, and has been working closely with industry on several projects in the areas of ridesharing, transportation, and integrated production and distribution planning. He serves as an associate editor of Operations Research, Production and Operations Management, IISE Transactions, NRL, and Networks.