Maximum Quadratic Assignment Problem: Reduction from Maximum Label Cover and LP-Based Approximation Algorithm

  • Konstantin Makarychev
  • Rajsekar Manokaran
  • Maxim Sviridenko
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6198)


We show that for every positive ε> 0, unless \({\mathcal NP} \subset {\mathcal BPQP}\), it is impossible to approximate the maximum quadratic assignment problem within a factor better than \(2^{\log^{1-\varepsilon} n}\) by a reduction from the maximum label cover problem. Then, we present an \(O(\sqrt{n})\)-approximation algorithm for the problem based on rounding of the linear programming relaxation often used in the state of the art exact algorithms.


Approximation Algorithm Linear Programming Relaxation Quadratic Assignment Problem Label Cover Heavy Edge 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Konstantin Makarychev
    • 1
  • Rajsekar Manokaran
    • 2
  • Maxim Sviridenko
    • 1
  1. 1.IBM Thomas J. Watson Research Center
  2. 2.Princeton UniversityPrinceton

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