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Updated: 1 hour 29 min ago

College of Engineering Graduate Commencement (Masters and Ph.D.), May 21

Tue, 2019-05-21 23:32
This ceremony includes all departments in the College of Engineering.

Bike to Work Day 2019, May 9

Thu, 2019-05-09 23:34
Happy Bike to Work Day 2019!

Pledge to Ride on Bike to Work Day, Thursday, May 9

Join the fun on the biggest bike day of the year! Pledge to ride and you’ll receive a map of Energizer Stations where you can get your free Bike to Work Day bag. You’ll also get $10 off at Mike’s Bikes!

Visit an Energizer Station to get your free Bike to Work Day bag. This handy canvas tote is filled with snacks, coupons, and useful information for your ride around town. Station hosts will provide tasty snacks and high fives to cheer on your morning ride.

This year, Berkeley's Campus Bike Committee will operate two Energizer Stations at Sproul Plaza (Bancroft and Telegraph) and at the Richmond Field near the Bay Trail from 7:00 a.m. - 9:30 a.m. Happy riding!

Chiwei Yan - Transportation Optimization: Data-enabled Advances in a Sharing Economy, Feb 11

Mon, 2019-02-11 23:33
Abstract: The transportation and logistics industries are undergoing a round of revolutionary innovation. This innovation is fueled by two key drivers: (1) the growing availability of data, and (2) new operational paradigms in a sharing economy. This talk focuses on showcasing how new models, enabled by the prevalence of data, can lead to significant value in operational decision-making.

We begin by presenting our research that shows how trip data in bike-sharing systems can be mined to infer rider substitution behaviors when there are bike or dock shortages. Based on a non-parametric ranking-based choice model, we propose efficient enumeration procedures and first-order methods to solve the large-scale estimation problem by exploiting problem structure. We prove consistency results of our method. We then demonstrate, with Boston Hubway data, that ridership can be significantly improved through effective inventory allocation operations with better demand modeling.

Next, we describe a recent work in which we propose a new car-pooling mechanism in ride-hailing, called dynamic waiting which varies rider waiting before dispatch. The goal is to limit price volatility in ride-hailing services by reducing the role of surge pricing. We describe a steady-state model depicting the long-run average performance of a ride-hailing service, and characterize the system equilibrium. Calibrating the model using Uber data, we reveal insights on welfare-maximizing pricing and waiting strategies. We show that, with dynamic waiting, price can be lowered, its variability is mitigated and total welfare is increased.

Bio: Chiwei Yan received his PhD from the Operations Research Center at MIT in 2017. His current research interest is in transportation and logistics, with a focus on data-driven optimization and emerging problems in a sharing economy. He is a recipient of the Best Dissertation Award Honorable Mention and the Outstanding Paper Award in Air Transportation from INFORMS Transportation Science and Logistics Society, the Best Dissertation Award from INFORMS Aviation Application Section, the AGIFORS Anna Valicek Award, and the UPS Doctoral Fellowship, among others. His research involves collaborations with both the private and public sectors, including the Federal Aviation Administration, Sabre Airline Solutions, Boston Hubway Bikes and Uber. Before coming to MIT, he obtained the Bachelor of Science in Industrial Engineering from Tsinghua University.

Sébastien Martin - From School Buses To Start Times: Driving Policy With Optimization, Feb 8

Fri, 2019-02-08 23:32
Abstract: Maintaining a fleet of buses to transport students to school is a major expense for U.S. school districts. In order to reduce costs by reusing buses between schools, many districts spread start times across the morning. However, assigning each school a time involves estimating the impact on transportation costs and reconciling additional competing objectives. Facing this intricate optimization problem, school districts must resort to ad hoc approaches, which can be expensive, inequitable, and even detrimental to student health. For example, there is medical evidence that early high school starts are impacting the development of an entire generation of students and constitute a major public health crisis. We present the first algorithm to jointly optimize school bus routing and bell time assignment. Our method leverages a natural decomposition of the routing problem, computing and combining subproblem solutions via mixed-integer optimization. It significantly outperforms state-of-the-art routing methods, and its implementation in Boston has led to $5 million in yearly savings, maintaining service quality for students despite a 50-bus fleet reduction. With the routing engine, we construct a tractable proxy to transportation costs, which allows the formulation of the bell time assignment problem as a multi-objective Generalized Quadratic Assignment Problem. Local search methods provide high-quality solutions, allowing school districts to explore tradeoffs between competing priorities and choose times that best fulfill community needs. In December 2017, the development of this method led the Boston School Committee to unanimously approve the first school start time reform in thirty years. In 2018, our collaboration with media and policy specialists generated an intense debate in Boston and many other cities on the use of OR tools for social good.

Bio: Sebastien Martin is a PhD candidate in Operations Research at MIT, advised by Prof. Dimitris Bertsimas and Patrick Jaillet. Beforehand, he obtained a MSc and BSc from Ecole Polytechnique in France. He has worked as a software engineering intern at Google Maps. His research focuses on large scale optimization, with applications in machine learning and transportation, and an emphasis on implementation and policy. His recent work, covered by the Wall Street Journal, the Boston Globe and Wired, led to major policy changes and millions of dollars in yearly saving for Boston and is a 2019 Edelman Award finalist.