e/Dead-end elimination

Information
has gloss	eng: The dead-end elimination algorithm (DEE) is a method for minimizing a function over a discrete set of independent variables. The basic idea is to identify "dead ends", i.e., "bad" combinations of variables that cannot possibly yield the global minimum and to refrain from searching such combinations further. Hence, dead-end elimination is a mirror image of dynamic programming and memoization, optimization techniques in which "good" combinations are identified and explored further. Although the method itself is general, it has been developed and applied mainly to the problems of predicting and designing the structures of proteins. The original description and proof of the dead-end elimination theorem can be found in .
lexicalization	eng: Dead end elimination
lexicalization	eng: dead-end elimination
instance of	e/Protein methods