A patented method for solving big problems

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Maximizing profits while minimizing costs is a top priority for organizations of every type. That may become a lot simpler, thanks to two UT Arlington industrial engineers.

Professor Bill Corley and Associate Professor Jay Rosenberger—both faculty members in the University’s Center on Stochastic Modeling, Optimization, and Statistics—have patented a method to solve linear programming problems.

Linear programming is a mathematical modeling technique used to help make quantitative decisions in business, engineering, and other fields. Solving these problems enables a more efficient allocation of resources. In the telecommunications industry, for example, linear programming can route cars in transit to their destinations in the quickest manner.

Linear programming is the most widely used computational model in the business and scientific worlds,” Dr. Corley says. “It will now become much more important. That’s the bottom line. We drastically improved more than 60 years of research for computing with this ubiquitous decision model.”

The patent uses a process called Constraint Optimal Selection Techniques to reduce the number of calculations needed to make an optimal decision, thus making it thousands of times faster to solve problems that have huge numbers of solution variables and restrictions. Such enormous problems previously could take weeks of computer time or exceed memory limitations.

It will also give answers to currently unsolvable nonlinear decision problems by approximating them with enormous linear programming problems,” Dr. Rosenberger adds.

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