About

Michael Trick is the Harry B. and James H. Higgins Professor of Operations Research at the Tepper School of Business, Carnegie Mellon University. He serves as the Dean of Carnegie Mellon University Qatar. His academic focus includes operations research, with an emphasis on applying data-informed, human-driven approaches to innovation and problem solving. As a faculty member, he is involved in research and thought leadership that connects artificial intelligence, machine learning, management science, and organizational behavior, reflecting the school's strategic vision to lead at the intersection of business, technology, and analytics.

Research topics

• Computer science
• Mathematical optimization
• Mathematics
• Operations research
• Theoretical computer science

Selected publications

• Michael Trick

  Authors group · 2020-01-22

  dataset1st authorCorresponding
  PublisherDOI

• Operations Research Enables Auction to Repurpose Television Spectrum for Next-Generation Wireless Technologies

  INFORMS Journal on Applied Analytics · 2019-01-01 · 11 citations

  article

  The authors describe a market-based two-stage auction that the FCC, with assistance from researchers from universities and consulting firms, developed. The two-sided auction repurposed 84 MHz of spectrum from conventional over-the-air TV to wireless uses and resulted in reducing the U.S. federal deficit by over $7 billion.

  PublisherDOI

• Integer and Constraint Programming Approaches for Round-Robin Tournament Scheduling

  Research Showcase @ Carnegie Mellon University (Carnegie Mellon University) · 2018-01-01 · 6 citations

  articleOpen access1st authorCorresponding

  Real sports scheduling problems are difficult to solve due to the variety of different constraints that might be imposed. Over the last decade, through the work of a number of researchers, it has become easier to solve round-robin tournament problems. These tournaments can then become building blocks for more complicated schedules. For example, we have worked extensively with Major League Baseball on creating “what-if” schedules for various league formats. Success in providing those schedules has depended on breaking the schedule into easily solvable pieces. Integer programming and constraint programming methods each have their places in this approach, depending on the constraints and objective function.

  PublisherOA PDFDOI

• Mathematical Models for Reconstruction Planning in Urban Areas

  Research Showcase @ Carnegie Mellon University (Carnegie Mellon University) · 2018-06-29 · 2 citations

  articleOpen access

  In the aftermath of a natural disaster, urban planners need to decide how neighborhoods should be restored under limited resources. An ill-planned reconstruction strategy and implementation process may result in socially inefficient land uses and subject neighborhoods to excessive future risk of disaster damage. In this study, we develop a prescriptive mathematical model for the design of redevelopment strategies that minimize future risk of flood and maximize net social benefit under spatial and equity constraints. This model, based on political districting models, is implemented using mathematical programming and a local search heuristic. Computational results are encouraging both for model outputs and solution efficiency. We generate an approximation to a Pareto frontier that provides decisionmakers with considerable flexibility regarding redevelopment strategies.

  PublisherOA PDFDOI

• Small Binary Voting Trees

  Figshare · 2018-06-30 · 7 citations

  articleOpen access1st authorCorresponding

  Sophisticated voting on a binary tree is a common form of voting structure, as exemplified by, for example, amendment procedures. The problem of characterizing voting rules that can be the outcome of this procedure has been a longstanding problem in social choice. We explore rules over a small number of candidates, and discuss existence and nonexistence properties of rules implementable over trees.

  OA PDFDOI

• A Linear Programming Approach to Solving Stochastic Dynamic Programming

  Research Showcase @ Carnegie Mellon University (Carnegie Mellon University) · 2018-01-01 · 34 citations

  articleOpen access1st authorCorresponding

  Tepper School of Business

  PublisherOA PDFDOI

• Introduction: 2016 Franz Edelman Award for Achievement in Operations Research and the Management Sciences

  INFORMS Journal on Applied Analytics · 2017-02-01

  articleOpen accessSenior author

  This special issue of Interfaces is devoted to the finalists of the 45th annual competition for the Franz Edelman Award for Achievement in Operations Research and the Management Sciences, the profession’s prestigious award for the practice of operations research and business analytics. As in previous years, the six finalists this year cover a wide range of industries and functions.

  PublisherOA PDFDOI

• Robust repositioning to counter unpredictable demand in bike sharing systems

  Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University) · 2016-07-09 · 40 citations

  article

  National Research Foundation (NRF) Singapore under International Research Centres in Singapore Funding Initiative

  Publisher

• Introduction: 2015 Franz Edelman Award for Achievement in Operations Research and the Management Sciences

  INFORMS Journal on Applied Analytics · 2016-02-01

  articleOpen accessSenior author

  This special issue of Interfaces is devoted to the finalists of the 44th annual competition for the Franz Edelman Award for Achievement in Operations Research and the Management Sciences, the profession’s prestigious award for the practice of operations research and business analytics. As in previous years, the six finalists this year cover a wide range of industries and functions.

  PublisherOA PDFDOI

• 2002), Solving the travelling tournament problem: A combined integer programming and constraint programming approach

  2015-10-30 · 20 citations

  articleSenior author

  Abstract. The Traveling Tournament Problem is a sports timetabling problem requiring production of a minimum distance double round robin tournament for a group of n teams. Even small instances of this prob-lem seem to be very difficult to solve. In this paper, we present the first provably optimal solution for an instance of 8 teams. The solution methodology is a parallel implementation of a branch and price algo-rithm that uses integer programming to solve the master problem and constraint programming to solve the pricing problem. Additionally, con-straint programming is used as a primal heuristic. 1

  Publisher

Frequent coauthors

• Anuj Mehrotra

  University of Miami

  11 shared

• Craig A. Tovey

  11 shared

• Rasmus V. Rasmussen

  Gentofte Hospital

  7 shared

• Donna Llewellyn

  6 shared

• John J. Bartholdi

  5 shared

• Hakan Yıldız

  Wayne State University

  5 shared

• Joseph Shantz

  University of Miami

  4 shared

• Edmund Burke

  4 shared

Education

• Ph.D., Operations Research

  University of British Columbia

  1984

• M.S., Operations Research

  University of British Columbia

  1981

• B.A., Mathematics

  University of British Columbia

  1978