please explain this algorithm

Given a complete probabilistic network G =(V,E,l) (i.e. with each edges e weighted by a likelihood  l(e) being a transmission link, e.g. l(e) ~ 1/d(e)), an α-spanning subnetwork (where α by default 95%) is a subnetwork N of G such that for any cut V= X+X’

(partitioning V into subset X and its complement X’=V-X), the sum of likelihoods of N-edges  cut is at least α% of the total likelihood of G-edges cut. We want to find minimum α-spanning subnetwork, which is the one with the minimum number of edges.

Problem of finding α-spanning subnetwork.

We can solve this problem either by ILP or by the following greedy heuristic:

N <- empty

α-SPAN: Sort all edges in ascending order of likelihoods l(e)

Delete edges until vertices are partitioned into two disjoint vertex subsets X and V-X

Sort all edges between X and V-X by likelihood in descending order and add them to N until  α% of the total likelihood is reached

Recursively apply α-SPAN for X and V-X

Квалификация: Алгоритмы, Программирование на C++, Java, Математика, Matlab and Mathematica

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( 14 отзыв(-а, -ов) ) atlanta, United States

ID проекта: #21886542

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hi there, the first algorithm is a version of min cut- max flow problem and the second one relies on transitivity of \alpha-span. Contact me for more details.

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