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O. Goldreich, S. Goldwasser and D. Ron, “Property Testing and Its Connection to Learning and Approximation Abstract,” Journal of the ACM, Vol. 45, No. 4, 1998, pp. 653-750. doi:10.1145/285055.285060

has been cited by the following article:

• TITLE: Optimal Approximation Algorithms for Reoptimization of Constraint Satisfaction Problems

  AUTHORS: Victor Alex Mikhailyuk

  KEYWORDS: C-Approximation Algorithm; Reoptimization; Approximation Resistant Predicates; Integrality Gap; Unique Games Conjecture (UGC)

  JOURNAL NAME: American Journal of Operations Research, Vol.3 No.2, March 28, 2013

  ABSTRACT: The purpose of reoptimization using approximation methods—application 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.