Events

"Optimal Delay Messages"

Presentation by Robert Shumsky
Professor of Operations Management
Tuck School of Business at Dartmouth

Wednesday, February 23
3:30pm - Graduate Seminar
4:30pm - Reception

About the seminar:

What should service providers tell their customers about delays? Typical prescriptions include ‘provide more accurate information’ or ‘under-promise and over-deliver,’ but there are few empirical studies to back up this advice and (to our knowledge) no rigorous models that capture the interplay between information provision and each customer’s emotional response. Customers are typically disappointed if they have to wait longer than expected, and may also value accuracy and precision in delay messages. We develop a framework that takes these preferences into account so that delay messages are designed to optimize the customers’ experiences while waiting. We assume that customers are Bayesian and update their beliefs about the expected start time of service, given both the messages from the service provider and the passage of time. They may be loss-averse in the sense that an increase in the expected wait causes more distress than the positive response caused by an equivalent decrease, and they may be uncertainty-averse in that variance in delay forecasts diminish utility. We find that when loss aversion dominates, the optimal message structure emphasizes provision of information about the tails of the distribution rather than simply updating the customers about the duration of the wait. When uncertainty-aversion is high, more traditional ordinal forecasts are optimal, and optimal messages should provide the most accurate information about the longest delays. In general, the model allows us to explore the role of forecasting systems and delay announcements to both provide accurate information and manage expectations.

"Optimal Delay Messages" (pdf)

Bio:

Robert Shumsky is a Professor of Operations Management at the Tuck School of Business at Dartmouth and is co-director of Dartmouth’s Master in Health Care Delivery Science program. His research focuses on the improvement of service operations, and he has written about capacity estimation and control, how to allocate work to improve quality, and how to coordinate service supply chains. He has conducted research on the U.S. air traffic management system and studied transportation operations for state agencies and the Federal Aviation Administration. He has also served as a consultant for both manufacturing and service operations, including call centers and health care providers. Professor Shumsky has published articles in Manufacturing and Service Operations Management, Operations Research, Management Science, and the Proceedings of the National Academy of Science. He currently serves in various editorial positions for several academic journals. He received his PhD degree in Operations Research from MIT.

"An Online Learning Approach to Dynamic Pricing and Capacity Sizing in Service Systems"

Presentation by Yunan Liu
Associate Professor
North Carolina State University

Wednesday, February 16
3:30pm - Graduate Seminar
4:30pm - Reception

About the seminar:

We study a dynamic pricing and capacity sizing problem in a queueing system, where the service provider’s objective is to obtain the optimal service fee p and service capacity μ so as to maximize cumulative expected profit (the service revenue minus the staffing cost and delay penalty). Due to the complex nature of the queueing dynamics, such a problem has no analytic solution so that previous research often resorts to heavy-traffic analysis where both the arrival rate and service rate are sent to infinity. In this work we propose an online learning framework designed for solving this problem which does not require the system’s scale to increase. Our framework is dubbed Gradient-based Online Learning in Queue (GOLiQ). GOLiQ organizes the time horizon into successive operational cycles and prescribes an efficient procedure to obtain improved pricing and staffing policies in each cycle using data collected in previous cycles. Data here include the number of customer arrivals, waiting times, and the server’s busy times. The ingenuity of this approach lies in its online nature, which allows the service provider to do better by interacting with the environment. Effectiveness of GOLiQ is substantiated by (i) theoretical results including the algorithm convergence and regret analysis (with a logarithmic regret bound), and (ii) engineering confirmation via simulation experiments.

“An Online Learning Approach to Dynamic Pricing and Capacity Sizing in Service Systems” (pdf)

Bio:

Yunan Liu is currently an Associate Professor at the Department of Industrial and Systems Engineering at North Carolina State University. He obtained his B.E. degree from the Electrical Engineering Department at Tsinghua University, M.S. and Ph.D. degrees from the Industrial Engineering and Operations Research Department at Columbia University. His research interests include stochastic modeling, applied probability, simulation, queueing theory, optimal control, and online learning, with applications to customer contact centers, health care, production, blockchain and transportation systems. He teaches graduate and undergraduate classes on stochastic models, simulations, queueing theory and reinforcement learning. His work was awarded the first place in the INFORMS Junior Faculty Interest Group Paper Competition in 2016.

"Innovative Uses of Drones for Last Mile Delivery with a Focus on Healthcare"

Presentation by Alice E. Smith
Joe W. Forehand/Accenture Distinguished Professor
Auburn University

Wednesday, February 9
3:00pm - Reception
3:30pm - Graduate Seminar 
Ford Hall, Room 110

*Required attendance for students in IE 8773 and 8774

About the seminar:

This seminar discusses two novel strategies for employing a combination of drones and delivery vehicles, such as trucks, for last mile delivery to homes and businesses. The work is general, but we aim for a healthcare application. One strategy uses drones to resupply trucks during the day for same day delivery, as orders are made available at a central depot. The trucks deliver the orders to the customers but do not have to return to the depot during the day since they are being supplied by the drones for new orders. The other strategy integrates a truck with a multi-capacity drone. In this case, either the truck or the drone can make both deliveries and pick-ups, and the drone is launched from and returned to the truck. A mathematical model is formulated and solved for each strategy. We show that both strategies offer benefits in customer service and cost of delivery compared to traditional truck delivery only. We focus our work on healthcare and specifically the delivery and pick up of medical supplies and tests (such as COVID tests) in challenged, rural environments. We are complementing our algorithmic and computational work with animations and a limited physical field trial.

“The traveling salesman problem with release dates and drone resupply” (pdf)

Bio:

Alice E. Smith is the Joe W. Forehand/Accenture Distinguished Professor of the Industrial and Systems Engineering Department at Auburn University, where she served as Department Chair from 1999-2011. She also has a joint appointment with the Department of Computer Science and Software Engineering. Previously, she was on the faculty of the Department of Industrial Engineering at the University of Pittsburgh from 1991-99, which she joined after industrial experience with Southwestern Bell Corporation. Dr. Smith has degrees from Rice University, Saint Louis University, and Missouri University of Science and Technology.

Dr. Smith’s research focus is analysis, modeling, and optimization of complex systems with emphasis on computation inspired by natural systems. She holds one U.S. patent and several international patents and has authored more than 200 publications which have garnered over 14,500 citations and an H Index of 47 (Google Scholar). She is the editor of the recent book Women in Industrial and Systems Engineering: Key Advances and Perspectives on Emerging Topics.

"Integrating Dual Scheduling Modes in Workforce Management"

Presentation by Karen Smilowitz
James N. and Margie M. Krebs Professor in Industrial Engineering and Management Sciences
Northwestern University

Wednesday, December 8
3:00pm - Reception
3:30pm - Graduate Seminar 
Ford Hall, Room 127

*Required attendance for students in IE 8773 and 8774

About the seminar:

Motivated by the emergence of self-scheduling platforms for volunteers and the continued need to meet time-specific needs of nonprofit organizations, this research explores modeling approaches and scheduling policies to effectively manage workforce scheduling for organizations with dual scheduling modes. As an illustrative example, we consider a nonprofit organization that provides relief to those impacted by disasters using both volunteers who schedule themselves and staff members who are assigned to shifts. We explore the advantages of scheduling policies that explicitly account for the two groups, balancing the need to cover time slots to meet demand with the desire to offer meaningful and convenient opportunities to volunteers such that they maintain their engagement with the organization. We present a case study based on operational data from our collaborators and more general insights based on synthetic data. This is joint work with Mariana Escallon-Barrios and Reut Noham.

Bio:

Dr. Karen Smilowitz is the James N. and Margie M. Krebs Professor in Industrial Engineering and Management Science at Northwestern University, with a joint appointment in the Operations group at the Kellogg School of Management. Dr. Smilowitz is an expert in modeling and solution approaches for logistics and transportation systems in both commercial and nonprofit applications. Dr. Smilowitz is the founder of the Northwestern Initiative on Humanitarian and Nonprofit Logistics. She has been instrumental in promoting the use of operations research within the humanitarian and nonprofit sectors through the Woodrow Wilson International Center for Scholars, the American Association for the Advancement of Science, and the National Academy of Engineering, as well as various media outlets. Dr. Smilowitz is the Editor-in-Chief of Transportation Science.