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H. Milton Stewart School of Industrial and Systems Engineering
H. Milton Stewart School of Industrial and Systems Engineering
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ItemRiding Technology Waves: Opportunities for Operations Research(Georgia Institute of Technology, 2017-03-30) Dietrich, BrendaBrenda Dietrich's talk includes a fly-by of five decades of information technology beginning with its use to automate business processes and extending to its current role in intermediating social processes. The resulting "data exhaust," together with the availability of low cost computing capacity, spawned the age of analytics, the rise of big data, and the birth of cognitive computing. The past, current, and potential role of operations research in these technology waves will be discussed.
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ItemAdventures in Policy Modeling!( 2016-03-28) Kaplan, Edward H.Policy Modeling refers to the application of operations research, statistics, and other quantitative methods to model policy problems. Recognizing that analyses of all sorts often exhibit diminishing returns in insight to effort, the hope is to capture key features of various policy issues with relatively simple “first-strike” models. Problem selection and formulation thus compete with the mathematics of solution methods in determining successful applications: where do good problems come from? how can analysts tell if a particular issue is worth pursuing? In addressing these questions, I will review some personal adventures in policy modeling selected from public housing, HIV/AIDS prevention, bioterror preparedness, suicide bombings and counterterrorism, in vitro fertilization, predicting presidential elections, and sports.
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ItemMultivariate Statistics and Machine Learning Under a Modern Optimization Lens(Georgia Institute of Technology, 2015-03-05) Bertsimas, DimitrisKey problems of classification and regression can naturally be written as optimization problems. While continuous optimization approaches has had a significant impact in statistics, discrete optimization has played a very limited role, primarily based on the belief that mixed integer optimization models are computationally intractable. While such beliefs were accurate two decades ago, the field of discrete optimization has made very substantial progress. Dr. Bertsimas will discuss how to apply modern first order optimization methods to find feasible solutions for classical problems in statistics, and mixed integer optimization to improve the solutions and to prove optimality by finding matching lower bounds. Specifically, he will report results for the classical variable selection problem in regression currently solved by LASSO heuristically, least quantile regression, and factor analysis. He will also present an approach to build regression models based on mixed integer optimization. In all cases he will demonstrate that the solutions found by modern optimization methods outperform the classical approaches. Most importantly, he suggests that the belief widely held in statistics that mixed integer optimization is not practically relevant for statistics applications needs to be revisited.
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ItemLessons Learned on Hard Work, Thinking Ahead, and Just Showing Up( 2014-10-09) Marshall, JohnThere is no such thing as an overnight success. Like the actor who does ten years of dinner theater before making it big, most of today’s leaders undergo significant challenges on the road to success. However, applying those insights can lead to significant growth. Join John Marshall, Senior Vice President and General Manager of AirWatch by VMware, as he shares how his experiences at Georgia Tech helped him take AirWatch from an apartment startup to a billion dollar buyout.
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ItemInteger Programming: the Global Impact(Georgia Institute of Technology, 2013-11-25) Nemhauser, George L.Integer programming is the (not very appealing or descriptive) name for optimization models and algorithms in which some variables are required to have integer values. Planning and operational problems in energy, finance, health, manufacturing, military, transportation, and in almost any imaginable domain where decisions are made, are formulated and solved using integer programming. For example, most Fortune 500 companies use integer programming in some aspects of their business. Currently available software is capable of solving models with thousands, and sometimes millions, of variables and constraints. We will discuss some integer programming models whose solutions have had big impact in solving important problems, and present recent progress that has made it possible to solve very large instances and to obtain provably good solutions quickly. We'll close by speculating on future advances in methodology and applications. Integer programming is the (not very appealing or descriptive) name for optimization models and algorithms in which some variables are required to have integer values. Planning and operational problems in energy, finance, health, manufacturing, military, transportation, and in almost any imaginable domain where decisions are made, are formulated and solved using integer programming. For example, most Fortune 500 companies use integer programming in some aspects of their business. Currently available software is capable of solving models with thousands, and sometimes millions, of variables and constraints. We will discuss some integer programming models whose solutions have had big impact in solving important problems, and present recent progress that has made it possible to solve very large instances and to obtain provably good solutions quickly. We'll close by speculating on future advances in methodology and applications.
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ItemI, Optimize: The Application of Industrial Engineering Principles to the Business of Entertainment(Georgia Institute of Technology, 2013-10-17) Primus, GuyThe entertainment industry is, by all accounts, more art than science. While entertainment will continue to be dominated by artists, those looking to improve upon the creative process have embraced the tools of industrial engineering, and industrial engineers have risen to the top of many creative organizations. Entertainment industry insider and ISyE graduate Guy Primus, IE 1992, MS IE 1995, provides a look behind the curtain of entertainment and shares case studies that demonstrate the principles of industrial engineering at work in the most artsy of industries.
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ItemService Engineering: Data-Based Science in Support of Service Management, or Empirical Adventures in Call Centers and Hospitals(Georgia Institute of Technology, 2011-02-24) Mandelbaum, AvishaiSynopsis: In this lecture, Dr. Mandelbaum will describe examples of complex service operations for which data-based simple models have been found useful, which he refers to as "Simple Models at the Service of Complex Realities." Examples include call centers, hospitals, banks, courts and more. He views these service systems through the mathematical lenses of Queueing Science, with a bias towards Statistics. The mathematical framework for his models is asymptotic queueing theory, where limits are taken as the number of servers increases indefinitely, in ways that maintain a sought-after (often delicate) balance between staffing level and offered-load. A specific such balance reveals an operational regime that achieves, under already moderate scale, remarkably high levels of both service quality and efficiency. This is the QED regime (Quality- & Efficiency- Driven), discovered by Erlang and substantiated mathematically by Halfin & Whitt. The data-source for the lecture is a unique data repository from call centers and hospitals. The data is maintained at the Technion's SEE Laboratory (Service Enterprise Engineering). It is unique in that it is transaction-based; it details the individual operational history of all the service transactions (e.g., calls in a call center or patients in an emergency department). One source of data, publicly available, is a network of four call centers of a U.S. bank, spanning two and a half years and covering about 1,000 agents; there are 218,047,488 telephone calls overall, out of which 41,646,142 were served by agents, while the rest were handled by answering machines. The data can be explored via SEEStat, an environment for online Exploratory Data Analysis. SEEStat is accessible here after registration.
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ItemLearning From the Experiences of Others(Georgia Institute of Technology, 2010-09-23) Efron, BradleyFamiliar statistical estimates such as batting averages, political polls, and medical trial results are obtained by direct observation of cases of interest. Sometimes, though, we can learn from the experience of "others": for instance there may be information about Player A's batting ability in the observed averages of Players B,C,D, etc. In his presentation, Professor Efron will present several examples showing how this works in practice, indicating some of the surprising theoretical ideas involved. The talk is mainly descriptive in nature, and is intended for a general scientific audience.
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ItemHooked on Optimization(Georgia Institute of Technology, 2010-09-16) Nemhauser, George L.Integer programming is addictive. I got hooked more than forty years ago and I'm still an addict. There are many fun challenges and no indication that the rate of progress has diminished. In this talk I'll tell a little of my story and conclude with what I think are current opportunities.
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ItemOperations Research and Homeland Security: From Models to Implementation(Georgia Institute of Technology, 2009-03-05) Wein, LawrenceDr. Lawrence Wein will address topics related to his research in public health and homeland security including: Preparedness and response to bio-terror anthrax attacks and to bio-terror attacks on food supply chains; Routes of transmission and infection control for pandemic influenza; Biometrics (e.g. fingerprint matching) to prevent terrorists from entering the country. The lecture will focus on modeling, policy recommendations, and implementations of these recommendations. During the presentation, Dr. Wein will also draw lessons about policy implementations from these examples and from examples from other homeland security work, including prevention of a bio-terror smallpox attack, nuclear weapons entering the country on a shipping container, nuclear weapons entering a city, and terrorist sneaking across the U.S. - Mexico border.