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Profile of George Nemhauser
 

George Nemhauser

 
Professor - School - Industrial, Systems Engineering - Georgia Institute of Technology
 
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Company Name : Georgia Institute of Technology
 
Company Website : www.gatech.edu
 
Company Address : Georgia Institute of Technology
, Atlanta, GA,
United States,
 
George Nemhauser Profile :
Professor - School - Industrial, Systems Engineering - Georgia Institute of Technology
 
George Nemhauser Biography :

He's assisted with the logistics for airlines and shipping ports, but a Georgia Tech professor is now responsible for ensuring the Yankees play the Red Sox in September.

George Nemhauser, the A. Russell Chandler Chaired Professor in Industrial and Systems Engineering, is one of the world's foremost experts on discrete optimization - a critical subject in relation to scheduling - and has published more than 100 papers and three books in this field. His book with Laurence Wolsey, "Integer Programming and Combinatorial Optimization," received the Lanchester Prize as the best publication in operations research in 1988. He was elected to the National Academy of Engineering in 1986.

Schedule-makers deal with conflicting requirements and preferences as a matter of course, but as the financial and competitive stakes in athletics at the college and professional level rise, so does the complexity of creating a balanced schedule. As a mathematician and a sports fan, Nemhauser noticed it could benefit from specialization.

He's a partner in a company that has handled athletic scheduling for several college conferences, including Tech's own Atlantic Coast Conference for nearly a decade. The objective, he said, is to balance the requirements of the television contract with competitive fairness while accommodating the needs of fans, coaches, players, media, sponsors, and facility operators.

Compared with collegiate scheduling, though, baseball is another order of magnitude. In fact, the complexity of the task makes it too large to handle as a whole. Developing a viable schedule, he noted, involved 12 high-performance computers running virtually non-stop for five months.

"It's a wildly constrained process and to come up with something feasible is very difficult," he said. "Perhaps IBM's Blue Gene computer could handle something as big and complicated as this, but I doubt it."

 
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