About

Michael O. Ball is Professor Emeritus at the Robert H. Smith School of Business at the University of Maryland. He holds a joint appointment within the Institute for Systems Research in the Clark School of Engineering and is a member of the Decision, Operations and Information Technologies Department within the Smith School. Dr. Ball has authored over 200 scholarly publications covering a range of subjects including air transportation, revenue management and pricing, supply chain management, and system reliability. He is the co-director and principal investigator of NEXTOR-III, an 8-university consortium funded by the FAA to conduct research in aviation operations research. Throughout his career, Dr. Ball has been involved in various research and consulting projects that have led to implementations in industry and government. In recent years, he has served on expert panels advising organizations such as the United Nations, the FAA, the National Academy of Engineering, and multiple airport authorities on aviation policies. He has been an active member of INFORMS, serving as area editor for Transportation and Optimization for Operations Research and currently as an associate editor for Operations Research and Transportation Science. Dr. Ball received BES and MSE degrees from Johns Hopkins University in 1972 and a PhD in Operations Research from Cornell University in 1977.

Research topics

• Computer Science
• Operations research
• Mathematics
• Mathematical optimization
• Microeconomics
• Economics
• Engineering

Selected publications

• Data Exploration by Representative Region Selection: Axioms and Convergence

  Mathematics of Operations Research · 2021-03-18 · 1 citations

  article

  We present a new type of unsupervised learning problem in which we find a small set of representative regions that approximates a larger data set. These regions may be presented to a practitioner along with additional information in order to help the practitioner explore the data set. An advantage of this approach is that it does not rely on cluster structure of the data. We formally define this problem, and we present axioms that should be satisfied by functions that measure the quality of representatives. We provide a quality function that satisfies all of these axioms. Using this quality function, we formulate two optimization problems for finding representatives. We provide convergence results for a general class of methods, and we show that these results apply to several specific methods, including methods derived from the solution of the optimization problems formulated in this paper. We provide an example of how representative regions may be used to explore a data set.

  PublisherDOI

• Causal analysis of flight en route inefficiency

  Transportation Research Part B Methodological · 2021-07-29 · 10 citations

  article
  PublisherDOI

• Incorporating User Preferences in Time-Based Flow Management Operations

  2020-10-11 · 1 citations

  articleSenior author

  This paper presents results of a simulation of strategies to incorporate business-driven airline preferences in metering operations. Traffic flow systems that balance demand versus capacity at busy airports assign Controlled Times of Arrival (CTAs) to incoming flights. We evaluate a strategy to assign these CTAs based on user-provided priority lists. The user-provided priority is used to drive a slot swapping algorithm that looks for opportunities to rearrange the order of flights in the CTA queue in a way that decreases delay cost. We quantify potential savings by comparing the queue after swapping with the default first-come-first-served rule. Simulations under a variety of realistic scenarios show that our proposed algorithm could reduce delay costs between 1.3% and 17% relative to a baseline where no swapping is performed. Opportunistic swapping, however, presents challenges when handling equity between carriers. Operational considerations and potential solutions to establish equity are discussed.

  PublisherDOI

• Facets of the Stochastic Network Flow Problem

  SIAM Journal on Optimization · 2020-01-01 · 3 citations

  articleSenior author

  We study a type of network flow problem that we call the minimum-cost F-graph flow problem. This problem generalizes the typical minimum-cost network flow problem by allowing the underlying network to be a directed hypergraph rather than a directed graph. This new problem is pertinent because it can be used to model network flow problems that occur in a dynamic, stochastic environment. We formulate this problem as an integer program, and we study specifically the case where every node has at least one outgoing edge with no capacity constraint. We show that even with this restriction, the problem of finding an integral solution is NP-hard. However, we can show that all of the inequality constraints of our formulation are either facet-defining or redundant.

  PublisherDOI

• Quantity-Contingent Auctions and Allocation of Airport Slots

  Transportation Science · 2020 · 29 citations

  1st authorCorresponding
  • Computer Science
  • Operations research
  • Computer Science

  In this paper, we define and investigate quantity-contingent auctions. Such auctions can be used when there exist multiple units of a single product and the value of a set of units depends on the total quantity sold. For example, a road network or airport will become congested as the number of users increase so that a permit for use becomes more valuable as the total number allocated decreases. A quantity-contingent auction determines both the number of items sold and an allocation of items to bidders. Because such auctions could be used by bidders to gain excessive market power, we impose constraints limiting market power. We focus on auctions that allocate airport arrival and departure slots. We propose a continuous model and an integer programming model for the associated winner determination problem. Using these models, we perform computational experiments that lend insights into the properties of the quantity-contingent auction.

  PublisherDOI

• Monge Properties, Optimal Greedy Policies, and Policy Improvement for the Dynamic Stochastic Transportation Problem

  INFORMS journal on computing · 2020-10-13 · 2 citations

  articleSenior author

  We consider a dynamic, stochastic extension to the transportation problem. For the deterministic problem, there are known necessary and sufficient conditions under which a greedy algorithm achieves the optimal solution. We define a distribution-free type of optimality and provide analogous necessary and sufficient conditions under which a greedy policy achieves this type of optimality in the dynamic, stochastic setting. These results are used to prove that a greedy algorithm is optimal when planning a type of air-traffic management initiative. We also provide weaker conditions under which it is possible to strengthen an existing policy. These results can be applied to the problem of matching passengers with drivers in an on-demand taxi service. They specify conditions under which a passenger and driver should not be left unassigned.

  PublisherDOI

• Equity and Strength in Stochastic Integer Programming Models for the Dynamic Single Airport Ground-Holding Problem

  Transportation Science · 2020 · 14 citations

  Senior authorCorresponding
  • Computer Science
  • Mathematical optimization
  • Computer Science

  We study stochastic integer programming models for assigning delays to flights that are destined for an airport whose capacity has been impacted by poor weather or some other exogenous factor. In the existing literature, empirical evidence seemed to suggest that a proposed integer programming model had a strong formulation, but no existing theoretical results explained the observation. We apply recent results concerning the polyhedra of stochastic network flow problems to explain the strength of the existing model, and we propose a model whose size scales better with the number of flights in the problem and that preserves the strength of the existing model. Computational results are provided that demonstrate the benefits of the proposed model. Finally, we define a type of equity property that is satisfied by both models.

  PublisherDOI

• Alternative resource allocation mechanisms for the collaborative trajectory options Program (CTOP)

  2019-01-01 · 1 citations

  articleSenior author

• Queensland Mining Journal analytics: new information from old data

  ASEG Extended Abstracts · 2019-11-11

  articleOpen accessSenior author

  SummaryThe Queensland Mining Journal represents a wealth of information relating to mining activities in the state, from 1800 to the present day. This material has been scanned and made available in the public domain as high-quality image files. We have applied Google Vision optical character recognition, parsed the output JSON files through a domain-specific filter and indexed the content for presentation via an analytics dashboard based on mineralogy and which can be filtered by commodity age and location. The dashboard further incorporates mine site information from Queensland’s Digital Exploration (QDEX) Data System allowing prospective miners to drill down into QDEX content based on mineral occurrence, mine status and deposit size. We plan to build on this activity using Elastic Search to improve our association of content from articles to spatial location.This activity supports individuals and mining companies with an interest in Queensland to rapidly identify locations of interest. It offers a pragmatic approach using freely available information to support the Queensland authorities in attracting investment to their region through lowering the barrier in terms of effort level for companies looking to explore in the state. This comes at a time of heightened competition for investment and could ultimately lead to increased exploration activity and success, resulting in brownfield development of historic prospects and mine sites, minimising environmental impact of new exploration and mining yet generating income for the state through local activity and tax revenue on any mineral extraction.

  PublisherOA PDFDOI

• Majority judgment over a convex candidate space

  Operations Research Letters · 2019-05-21 · 1 citations

  articleOpen access
  PublisherOA PDFDOI

Recent grants

• DDDAS-SMRP: Dynamic Real-Time Order Promising and Fulfillment for Global Make-to-Order Supply Chains

  NSF · $633k · 2006–2010

Frequent coauthors

• Alexander Estes

  University of Maryland, College Park

  15 shared

• David J. Lovell

  13 shared

• Mark Hansen

  12 shared

• Vinai S. Trichur

  Akamai (United States)

  11 shared

• Zhenying Zhao

  Suzhou Institute of Biomedical Engineering and Technology

  11 shared

• John S. Baras

  10 shared

• Yufeng Tu

  Shanghai Ninth People's Hospital

  10 shared

• Wolfgang Jank

  University of South Florida

  10 shared

Education

• PhD, Operations Research

  Cornell University

  1977

Awards & honors

• Smith Provides PhD Fellowships Named for Michael Ball