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Amelia Regan

Amelia Regan

Director, Master of Supply Chain Transportation and Logistics at University of Washington

Amelia Regan, Professor Emerita of Computer Science and Transportation Systems Engineering at the University of California, Irvine, recently took on a new position as the director of the Master in Supply Chain Transportation and Logistics at the University of Washington. Her current research interests include robot routing in automated warehouses, optimal contracting for freight transportation, logistics systems optimization, machine learning tools for logistics systems, technologies enabling automated driving, pedestrian and cyclist safety and sustainable transportation systems. Her research has been supported by various sources including the National Science Foundation, the Transportation Research Board and JB Hunt Inc., and has been published in more than 175 refereed journal articles and conference proceedings. Before her career in academia she was a software engineer and research analyst with UPS and the Association of American Railroads. She is a collaborator and advisor to Next Generation Robotics (, a new logistics optimization company.
Track: Retail

Faster Exact Methods for Large Scale Real-time Logistics Operations — Implications for Practice

Problems arising in warehousing and distribution continue to grow in size and complexity. In addition, we may finally be at an inflexion point in which automation will finally impact all corners of large scale logistics operations. While many metaheuristics or simpler techniques can be helpful in solving the many combinatorial optimization problems that arise, our progress in improving the speed of column generation (exact methods) for solving large scale integer linear programs means that these methods will soon be practical for problems such as capacitated vehicle routing (with and without time windows or deadlines), robot routing (with and without human handlers) in single- and multi-level warehouses and product placement problems which are a key to effective large-scale fulfillment operations. This talk will present a number of problems, some details about our new pre-computing methods that result in remarkable (10-100X) speedups and our plans for implementation of these methods in practice.