Events

ISyE Seminar Series: Alice Smith

Alice Smith

"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.

 

ISyE Seminar Series: Yunan Liu

Yunan Liu

"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
3:00pm - Reception
3:30pm - Graduate Seminar

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.