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New Algorithm Provides Huge Speedups For Optimization Problems (mit.edu)
An anonymous reader writes: MIT graduate students have developed a new "cutting-plane" algorithm, a general-purpose algorithm for solving optimization problems. They've also developed a new way to apply their algorithm to specific problems, yielding orders-of-magnitude efficiency gains. Optimization problems look to find the best set of values for a group of disparate parameters. For example, the cost function around designing a new smartphone would reward battery life, speed, and durability while penalizing thickness, cost, and overheating. Finding the optimal arrangement of values is a difficult problem, but the new algorithm shaves a significant amount of operations (PDF) off those calculations. Satoru Iwata, professor of mathematical informatics at the University of Tokyo, said, "This is indeed an astonishing paper. For this problem, the running time bounds derived with the aid of discrete geometry and combinatorial techniques are by far better than what I could imagine."
You never know; I'm sure he had plenty of 1UPs.
How can I believe you when you tell me what I don't want to hear?
Math is hard.
Or, more accurately, math is believed to be hard.
sub f{($f)=@_;print"$f(q{$f});";}f(q{sub f{($f)=@_;print"$f(q{$f});";}f});
I read the summary. I didn't understand it. Then I read the article. I didn't understand it either.
I am an inconsiderate clod you... Oh, wait...
In Soviet Russia inconsiderate clods you?
"So long and thanks for all the fish."