Friday, January 17, 2014

MIT's new algorithm could solve thorny optimization problems

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A group of researchers at the Massachusetts Institute of Technology have devised a potentially more effective way of helping computers solve some of the toughest optimization problems they face.

Their new algorithm is more computationally effective than other approaches, because it scales in a "near-linear" fashion, according to Jonathan Kelner, an associate professor of applied mathematics at MIT and a member of MIT's Computer Science and Artificial Intelligence Laboratory, who co-authored the new algorithm.

"The running times for previously known algorithms scaled substantially worse than linearly," Kelner wrote by email, meaning that as a problem becomes more complex, the performance of the computer undertaking the problem slows dramatically.

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