Sufficient Global Optimality Conditions for Bivalent Quadratic Optimization
M.C. PINAR (mustafapbilkent.edu.tr)
Abstract: We prove a sufficient global optimality condition for quadratic optimization with quadratic constraints where the variables are allowed to take -1 and 1 values. We extend the condition to quadratic programs with matrix variables and orthogonality conditions, and in particular, to the quadratic assignment problem.
Keywords: nonconvex quadratic programming with bivalent variables, sufficient condition, global optimality
Category 1: Nonlinear Optimization (Quadratic Programming )
Category 2: Integer Programming (0-1 Programming )
Citation: Bilkent University Technical Report, September 2002.
Entry Submitted: 09/16/2002
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