 
Giant global corporations use them to figure out their
supply chain problems, governments use them to work on
emergency preparedness plans, farmers use them to figure out
what crops to plant and when, and the military uses them to
figure out sophisticated deployment and logistics plans. But
they’re also used to figure out the best way to tour through
DisneyWorld, or how to load a truck with goods so that they
can be off-loaded in proper order. They’re decision models,
and they’re used to help people and companies optimize their
choices.
Decision models are a common tool in the field of
operations research, which uses data and mathematical
techniques to solve specific business problems. Saul I. Gass,
professor emeritus of management science, is a pioneer in
the field of operations research. Gass helped develop the
technique of linear programming, a simple but powerful tool
that allows researchers to create decision models. The power
of linear programming is both its remarkable flexibility and
its power to model a large range of tremendously complex
problems.
Today it seems natural to have computer programmers,
mathematicians and engineers working on business problems.
But it was a revolutionary idea in the 1960s, when Gass and
his colleagues first transplanted techniques and models
developed for the military sector to the private sector
business, starting with the oil refinery industry. His work
went on to have an enormous impact across a variety of
fields.
Gass is also known for mentoring following generations of
operations researchers and for acting as an ambassador for
the field. “Saul had an uncanny ability to explain the
methodology,” says Frank Alt, associate professor of
management science and statistics. His layman-friendly book
Linear Programming is one of the only computer programming
textbooks to use cartoons to explain its concepts. Gass
later explained the origin, applicability and drawbacks of
models in a series of papers titled “Model World.”
Gass’ Smith School colleagues are continuing to provide
thought leadership—as well as real solutions to real
problems—in operations research. Bruce Golden,
France-Merrick Professor of Management Science, recently
worked with the University of Maryland Hospital’s cardiac
surgery department to optimize the number of beds in the
intensive care unit (ICU), where there is one nurse per bed,
and the remote telemetry unit, where less staff is required.
“You can’t perform surgery if all of the ICU beds are taken,
and if all the remote telemetry beds are occupied, then you
can’t move patients from the ICU into the less expensive
ward,” says Golden. “So it’s important to get the mix of
beds right. Our model was able to save the hospital about $3
million on paper.” Michael Fu, professor of management
science, is working with the FDIC to evaluate each of its
6,000 member banks in order to determine level of premium to
charge for FDIC insurance.
What kinds of problems will operations research solve in
the future? “The emergence of new fields creates
opportunities for the use of mathematical models,” says Alt.
“We can’t always predict what those new fields will be, but
we can predict that there will always be the increased need
for models and their analysis.”
Interested in learning more? A new book, Perspectives
in Operations Research: Papers in Honor of Saul Gass’ 80th
Birthday, co-edited by Alt, Fu, and Golden, was
published by Springer as part of its “Research/Computer
Science Interfaces” series. The first part of the book
provides a sweeping overview of the history of the
operations research field and Gass’ contributions, while the
second part is a sampling of current research topics in the
field. Papers were contributed by a bevy of distinguished
scholars in operations research. |
