Using Bit Representation to Improve LP Relaxations of Mixed-Integer Quadratic Programs

نویسندگان

  • Laura Galli
  • Adam N. Letchford
  • Daniel J. Grainger
چکیده

A standard trick in integer programming is to replace each bounded integer-constrained variable with a small number of binary variables, using the bit representation of the given variable. We show that, in the case of mixed-integer quadratic programs (MIQPs), this process can enable one to obtain stronger linear programming relaxations. Moreover, we give a simple sufficient condition under which one can use bit representation to convert a (not necessarily convex) MIQP into a mixed 0-1 linear program of polynomial size.

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تاریخ انتشار 2017