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Lagrangean Approximation for Combinatorial Inverse Problems

By Hasmik Sahakyan and Levon Aslanyan

Abstract

Various combinatorial problems are effectively modelled in terms of (0,1) matrices. Origins are coming from n-cube geometry, hypergraph theory, inverse tomography problems, or directly from different models of application problems. Basically these problems are NP-complete. The paper considers a set of such problems and introduces approximation algorithms for their solutions applying Lagragean relaxation and related set of techniques

Topics: Approximation Algorithms, Lagragean Relaxation
Publisher: Institute of Information Theories and Applications FOI ITHEA
Year: 2008
OAI identifier: oai:sci-gems.math.bas.bg:10525/999
Journal:

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