Seminar: Data Privacy in Bid-Price Control for Network Revenue Management by İlker Birbil


 Data Privacy in Bid-Price Control for Network Revenue Management

İlker Birbil

Econometric Institute, Erasmus School of Economics
Erasmus University, Rotterdam


We present a network revenue management problem where multiple parties agree to share some of the capacities of the network. This collaboration is performed by constructing a large mathematical programming model available to all parties. The parties then use the solution of this model in their own bid-price control systems. In this setting, the major concern for the parties is the privacy of their input data and the optimal solutions containing their individual decisions. To address this concern, we propose an approach based on solving an alternative data-private model constructed with input masking and random transformations. Our main result shows that each party can safely recover only its own optimal decisions after the same data-private model is solved by each party. We also discuss several special cases where possible privacy leakage would require attention. Observing that the dense data-private model may take more time to solve than the sparse original non-private model, we further propose a modeling approach that introduces sparsity into the data-private model. We support our results with a simulation study where we use a real-world network structure. The talk ends with a discussion on a decomposition approach that we have recently started to work on.

Short Bio: 

Ilker Birbil is a faculty member in Erasmus University Rotterdam at the Econometric Institute, where he serves as an endowed professor for the Chair in Data Science and Optimization. He received his PhD degree from North Carolina State University, Raleigh, USA. He then worked for two years as a postdoctoral research fellow in Erasmus Research Institute of Management, Rotterdam, The Netherlands. His research interests include parallel and distributed optimization in machine learning, algorithm development for large-scale optimization problems, data science, revenue management, stochastic dynamic programming. Lately, he is interested in data privacy in decision making.

All interested are cordially invited.  

DATE    : Friday, January 31, 2020 
TIME    : 15:00-16:00 
ROOM  : VYKM 2, 5th floor of Engineering Building (Perkins Hall)