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Optimal Approximation Algorithms for Reoptimization of Constraint Satisfaction Problems
Author(s) -
V. A. Mikhailyuk
Publication year - 2013
Publication title -
american journal of operations research
Language(s) - English
Resource type - Journals
eISSN - 2160-8849
pISSN - 2160-8830
DOI - 10.4236/ajor.2013.32025
Subject(s) - approximation algorithm , mathematics , relaxation (psychology) , combinatorics , constraint satisfaction problem , mathematical optimization , algorithm , discrete mathematics , psychology , social psychology , statistics , probabilistic logic

The purpose of reoptimization using approximation methodsapplication of knowledge about the solution of the initial instance I, provided to achieve a better quality of approximation (approximation ratio) of an algorithm for determining optimal or close to it solutions of some “minor” changes of instance I. To solve the problem Ins-Max-EkCSP-P (reoptimization of Max-EkCSP-P with the addition of one constraint) with approximation resistant predicate P exists a polynomial threshold (optimal) -approximation algorithm, where the threshold random approximation ratio of P). When the unique games conjecture (UGC) is hold there exists a polynomial threshold (optimal) -approximation algorithm (where and the integrality gap of semidefinite relaxation of Max-EkCSP-P problem Z) to solve the problem Ins-Max-EkCSP-P.

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