Prizes

UPS George D. Smith Prize

The George D. Smith Prize is aimed at strengthening ties between academia and industry by rewarding institutions of higher education for effective and innovative preparation of students to be good practitioners of operations research. The Prize is generously underwritten by UPS. Awarded for the first time in 2012, past winners are University of Cincinnati – Operations, Business Analytics and Information Systems Department; MS in Business Analytics Program, Haslam College of Business, University of Tennessee; U.S. Air Force Academy, Operations Research Program; Carnegie Mellon University, H. John Heinz III College; Sauder School of Business, University of British Columbia – Center for Operations Excellence; MIT Leaders for Global Operations; Naval Postgraduate School, and Tauber Institute for Global Operations at University of Michigan.  The 2020 Competitors will be announced in early 2020.

The teams will present their work to the judges on Sunday, April 26.

The Smith Prize winner will be announced at the Edelman Gala on Monday, April 27.  The 2020 winner will give their presentation on Tuesday, April 28 in the INFORMS Prizes & Special Sessions Track.

Go to https://www.informs.org/Recognizing-Excellence/INFORMS-Prizes/UPS-George-D.-Smith-Prize for more information.

Daniel H. Wagner Prize for Excellence in Operations Research

The Daniel H. Wagner competition is held each fall at the INFORMS Annual Meeting. The 2019 Wagner Prize Reprise will take place on Monday, April 27 in the INFORMS Prizes & Special Sessions Track.

The 2019 Wagner winner is Didi for their project “Ride-hailing Order Dispatching at DiDi via Reinforcement Learning.” Order dispatching is instrumental to the marketplace engine of a large-scale ride-hailing platform like DiDi, which continuously matches passenger trip requests to drivers at a scale of tens of millions per day. Due to the dynamic and stochastic nature of supply and demand in this context, the ride-hailing order dispatching problem is very challenging to solve for an optimal solution. Added to the complexity are considerations of system response time, reliability, and multiple objectives. In this paper, we describe how our approach to this optimization problem has evolved from a combinatorial optimization approach to one that encompasses a semi-MDP model and deep reinforcement learning. We discuss the various practical considerations of our solution development and real-world impact to the business.

This prize emphasizes the quality and coherence of the analysis used in practice. Dr. Wagner strove for strong mathematics applied to practical problems, supported by clear and intelligible writing. The Wagner Prize recognizes those principles by emphasizing good writing, strong analytical content and verifiable practice successes. The competition is held and the winner is announced at the INFORMS Annual Meeting in the fall.

Past awardees include practitioners and researchers from Cornell University; Lehigh University and the Pennsylvania Department of Corrections; Linkoping Institute of Technology, The Forestry Research Institute of Sweden, CDC, Ford, U.S. Coast Guard, Intel, IBM T. J. Watson Research, Schneider National, Boston University, University of Florida, and others.

To find out more, go to https://www.informs.org/Recognizing-Excellence/INFORMS-Prizes/Daniel-H.-Wagner-Prize-for-Excellence-in-Operations-Research-Practice.

Innovative Applications in Analytics Award 

Brought to you by the Analytics Society of INFORMS, Kinaxis, and Adelphi University.

The IAAA Finalists will present on Tuesday, April 28 in the INFORMS Prizes & Special Sessions Track. The winner will be announced at the conference.

The teams competing for the 2020 IAAA will be announced in early February 2020.

The purpose this award is to recognize the creative and unique application of a combination of analytical techniques in a new area. The prize promotes the awareness and value of the creative combination of analytics techniques in unusual applications to provide insights and business value. The Analytics Section leadership would like to cordially thank all the members of the judging committee for their hard work in selecting these finalists.

To find out more, go to https://www.informs.org/Recognizing-Excellence/Community-Prizes/Analytics-Society/Innovative-Applications-in-Analytics-Award.

INFORMS O.R. & Analytics Student Team Competition

Finalist Competition – Conference attendees invited!

The finalists will present on Monday, April 27.

INFORMS introduced the O.R. & Analytics Team Competition in 2017 to highlight young talent and provide O.R. and analytics students the opportunity to solve the kinds of real-world workplace challenges they will face during their careers.

Teams made up of undergraduate and master’s student are given the same business problem, data sets, and access to software to solve a challenging problem using an OR/analytics approach. A panel of industry and academic experts judge written submissions based on teams’ use of the full analytics process, from framing the problem to methodology selection, data use, model building and innovation. Teams selected as finalists present their solutions to a judging panel at the conference with the winners announced on-site.

The 2020 competition problem, sponsored by Title Sponsor Bayer, challenges students to design a manufacturing distribution network that involves determining product flows in the presence of resource capacity constraints. The problem provides realistic data for students to perform statistical analyses, develop simulation models and/or machine learning, design the distribution network using optimization, and conduct a quantitative assessment of their solution.

To find out more, go to http://connect.informs.org/oratc/home.

Syngenta Crop Challenge in Analytics

The population of Earth is growing daily and our world is running out of land needed to produce food. Meanwhile, the crops farmers plant face escalating challenges due to increasingly variable growing conditions and climate change.

Today, the agriculture industry works to optimize the amount of food we gain from plants by breeding plants with the strongest, highest-yielding genetics. Scientists at R&D organizations like Syngenta create stronger plants by breeding and then selecting the best offspring over time to provide to farmers. Data-driven strategies can help our industry breed better seeds, faster. Developing models that identify robust patterns in our experimental data may help scientists more accurately choose seeds that increase the productivity of the crops we plant – and help address the growing global food demand.

How can we use data to address the growing global food demand?

The finalists will present on Monday, April 27. The winner will be announced at the conference.

For more information, go to https://www.ideaconnection.com/syngenta-crop-challenge/.