Collaborative optimization simplifies real-world problems

Posted on 06. Oct, 2011 by in Academic Departments, Annual Report, Industrial and Systems Engineering, Issues, Research

Of the 10 themes that make up the core research program at the new Wisconsin Institutes for Discovery (WID), the mathematical optimization group is especially well positioned to have a multidisciplinary impact at the institutes and beyond.

The team is a blend of industrial and systems engineering and computer sciences faculty and will expand to include experts from other fields in the next year. Led by Professor Michael Ferris (also computer sciences), the group includes Industrial and Systems Engineering Associate Professor Jeffrey Linderoth and Assistant Professor Jim Luedtke, along with Professor Stephen Wright (also computer sciences) and Computer Sciences and Electrical and Computer Engineering Assistant Professor Ben Recht.

The WID group brings together a rare combination of researchers with a variety of optimization specialties who will study and develop new methods, as well as apply these methods, to a wide range of important real-world problems. The team’s dual emphasis on research and applications makes it unique.

Optimization experts tend to specialize in tackling problems that involve either discrete variables, which are essentially yes or no decisions, or continuous variables, where design parameters fall along a continuum of values. Such optimization teams at other institutions tend to have expertise in one class of problems or the other.  The WID team has experts in both.

To tackle real-world issues, the researchers will translate problems into mathematical equations that can be solved and analyzed, and develop the optimization methods for solving these problems. The team will work closely with other researchers to expand the use of optimization methods to their WID-sponsored projects, such as systems biology, epigenetics or medical devices. “UW-Madison has a long tradition of being a world-leading institution in mathematical optimization, and the institute will allow us to continue this tradition,” Linderoth says.

The group also will study complex problems beyond WID. Examples of ongoing projects include better-targeted radiation for cancer treatments, more efficient operating room scheduling in hospitals, and designs for more reliable electric grids. “The optimization group embodies the collaborative mission of WID,” Ferris says. “Our tools and techniques will provide a direct benefit to our collaborators, allowing them to more efficiently analyze and effectively model their data, whether the subject and variables are drawn from ecology, medicine, statistics, agriculture, engineering or genetics.”

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