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K-approximation of k-hitting set : ウィキペディア英語版
K-approximation of k-hitting set
In computer science, k-approximation of k-hitting set is an approximation algorithm for weighted hitting set. The input is a collection ''S'' of subsets of some universe ''T'' and a mapping ''W'' from ''T'' to non-negative numbers called the weights of the elements of ''T''. In k-hitting set the size of the sets in ''S'' cannot be larger than ''k''. That is, \forall i \in S: |i| \leq k. The problem is now to pick some subset ''T''' of ''T'' such that every set in ''S'' contains some element of ''T''', and such that the total weight of all elements in ''T''' is as small as possible.
==The algorithm==
For each set j in ''S'' is maintained a ''price'', p_j, which is initially 0. For an element ''a'' in ''T'', let ''S''(''a'') be the collection of sets from ''S'' containing ''a''. During the algorithm the following invariant is kept
:\forall a \in T: \sum_ p_j \leq W(a).\,
We say that an element, ''a'', from ''T'' is ''tight'' if \Sigma_ p_j = W(a). The main part of the algorithm consists of a loop: As long as there is a set in ''S'' that contains an element from ''T'' which is not tight, the price of this set is increased as much as possible without violating the invariant above. When this loop exits, all sets contain some tight element. Pick all the tight elements to be the hitting set.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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