Cutting Planes for Mixed 0-1 Semidefinite Programs

  • G. Iyengar
  • M. T. Çezik
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2081)

Abstract

Since the seminal work of Nemirovski and Nesterov [14], research on semidefinite programming (SDP) and its applications in optimization has been burgeoning. SDP has led to good relaxations for the quadratic assignment problem, graph partition, non-convex quadratic optimization problems, and the TSP. SDP-based relaxations have led to approximation algorithms for combinatorial optimization problems such as the MAXCUT and vertex coloring. SDP has also found nu- merous applications in robust control and, as a natural extension, in robust op- timization for convex programs with uncertain parameters. For a recent survey of semidefinite techniques and applications see [20].

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • G. Iyengar
    • 1
  • M. T. Çezik
    • 2
  1. 1.IEOR DeptColumbia UniversityNYUSA
  2. 2.Bell LaboratoriesLucent TechnologiesHolmdelUSA

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