No Free Lunch Theorem:

No Free Lunch Theorem: "states that any two optimization algorithms are equivalent when their performance is averaged across all possible problems."

i.e. any heuristic is the same as any other when averaged across infinite number of cases.

Definitions:

Six Sigma: Six Sigma seeks to improve the quality of process outputs by minimizing variability in manufacturing and business processes, and identifying and removing the causes of defects (errors). (reduce variability to increase production quality)
Fisher's fundamental theorem: The rate of increase in fitness of any organism at any time is equal to its genetic variance in fitness at that time. (More variance = better at adapting)

When use them??

Use Six Sigma to reduce variation when rugged landscape is fixed.
--> Concentrate when not much in environment changes.

Use Fisher's fundamental theorem when rugged landscape moves.
More variation allows for more chance of adpation.
--> Variance when environment has changed a lot.




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http://en.wikipedia.org/wiki/Adaptive_landscapes
http://en.wikipedia.org/wiki/Hill_climbing