Integer Programming and Combinatorial Optimization

Volume 2081 of the series Lecture Notes in Computer Science pp 251-263


Cutting Planes for Mixed 0-1 Semidefinite Programs

  • G. IyengarAffiliated withIEOR Dept, Columbia University
  • , M. T. ÇezikAffiliated withBell Laboratories, Lucent Technologies

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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].