Awarded 2018 INFORMS Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research
Catonsville, MD, November 21, 2018 – INFORMS, the leading association for operations research (O.R.) and analytics professionals, has awarded the 2018 INFORMS Daniel H. Wagner Prize for Excellence in Practice of Advanced Analytics and Operations Research to researchers from Cornell University for their work to increase the efficiency of bike-sharing programs. The award was presented at the 2018 INFORMS Annual Meeting held in Phoenix, AZ on November 4-7.
As urban populations continue to grow, as well as congestion and commuter traffic, eco-friendly alternative transportation options are becoming increasingly popular. In cities around the world, bike-sharing programs have become an accessible method to travel from place to place quickly and efficiently.
The prize-winning paper Analytics and Bikes: Riding Tandem with Motivate to Improve Mobility, which provided unique application of analytics and O.R. to improve the placement of bike docking stations and create an inventive approach to replenish and rebalance these docking stations, was presented by Daniel Freund, Shane G. Henderson, and David B. Shmoys and Eoin O'Mahony.
The researchers worked with Motivate, the operator of the largest bike sharing system found in New York, Chicago and San Francisco, to develop an initiative to improve the allocation of docks to stations, and then create an incentive scheme to crowd source rebalancing called Bike Angels.
Both of these projects have been fully implemented to improve the performance of Motivate’s systems across the country: Motivate has moved hundreds of docks in its systems nationwide and the Bike Angels program now aids rebalancing in San Francisco and NYC. In NYC, Bike Angels yields improvement comparable to that obtained through Motivate’s traditional rebalancing efforts, at far less financial and environmental cost.
The award was presented during the 2018 INFORMS Annual Meeting in Phoenix, AZ, which attracted more than 6,000 students, academics, professionals, and industry leaders from around the world.
This year was a special year for the Wagner judging committee because they decided to award a second place to Combinatorial Exchanges for Trading Fishery Access Rights by Martin Bichler and Vladimir Fux of the Technical University of Munich; Douglas Ferrell of the Department of Primary Industries, New South Wales; and Jacob K. Goeree of the University of New South Wales.The elegant and innovative mathematics of this work addresses the environmental concern of overfishing by implementing in New South Wales a first-of-a-kind market design for the reallocation of catch shares and the largest combinatorial exchange to date. The market design addresses previous solution weaknesses of lack of participation and fair payments. The implemented exchange illustrates how computational optimization and market design can provide policy tools to solve complex policy problems considered intractable only a few years ago. The exchange operated from May to July 2017.
The additional finalists for the 2018 award were:
- What's Wrong with My Dishwasher: Advanced Analytics Improve the Diagnostic Process for Miele Technicians by Segev Wasserkrug, Yiashai Feldman, Evgeny Shindin, and Sergey Zeltyn of IBM; and Martin Kreuger of Miele
- Primal-Dual Algorithms for Order Fulfillment at Urban Outfitters, Inc. by John M. Andrews, Vivek F. Farias, Aryan I. Khojandi, and Chad M. Yan of Celect
- Centralized Admissions for Engineering Colleges in India by Surender Baswana of the Indian Institute of Technology Kanpur; Partha Pratim Chakrabarti of the Indian Institute of Technology Kharagpur; Sharat Chandran of the Indian Institute of Technology Bombay; Yash Kanoria of Columbia Business School; and Utkarsh Patange of the Indian Institute of Technology Kanpur and Alphagrep Securities
- Collaborative Human-UAV Search and Rescue for Missing Tourists in Nature Reserves by Yu-Jun Zheng and Wei-Guo Sheng of Hangzhou Normal University; Yi-Chen Du of Zhejiang University of Technology; and Hai-Feng Ling of Army Engineering University
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