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Strong lower bounds on the approximability of some NPO PB-complete maximization problems

  • Viggo Kann
Contributed Papers Complexity Theory
Part of the Lecture Notes in Computer Science book series (LNCS, volume 969)

Abstract

The approximability of several NP maximization problems is investigated and strong lower bounds for the studied problems are proved. For some of the problems the bounds are the best that can be achieved, unless P = NP.

For example we investigate the approximability of Max PB 0 – 1 Programming, the problem of finding a binary vector x that satisfies a set of linear relations such that the objective value Σc i x i is maximized, where c i are binary numbers. We show that, unless P = NP, Max PB 0 – 1 Programming is not approximable within the factor n1−ε for any ε>0, where n is the number of inequalities, and is not approximable within \(m^{1/2 - \varepsilon }\)for any ε>0, where m is the number of variables.

Similar hardness results are shown for other problems on binary linear systems, some problems on the satisfiability of boolean formulas and the longest induced circuit problem.

Keywords

Maximization Problem Performance Ratio Truth Assignment Boolean Formula Strong Lower Bound 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Viggo Kann
    • 1
  1. 1.Department of Numerical Analysis and Computing ScienceRoyal Institute of TechnologyStockholmSweden

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