Computer Scientists Find a Key Research Algorithm's Limits The most widely used technique for optimizing values of a math function turns out to be a fundamentally difficult computational problem.

The algorithm worked with an accuracy of 0.999 and a precision of 0.9984. That’s significant because it sets up the possibility of an automated process for spotting “interesting” sequences.

In such cases, the fastest known shortest-path algorithm doesn’t work. For decades, fast algorithms for finding shortest paths on negative-weight graphs have remained elusive.

The new algorithm handles changes consisting of deleted edges -- for example, if the equivalent of a stretch of a road suddenly becomes inaccessible due to roadworks.