Sensitivity theorems in integer linear programming
Mathematical Programming: Series A and B
Some proximity and sensitivity results in quadratic integer programming
Mathematical Programming: Series A and B
Convex separable optimization is not much harder than linear optimization
Journal of the ACM (JACM)
The relationship between integer and real solutions of constrained convex programming
Mathematical Programming: Series A and B
Global Optimization Techniques for Solving the General Quadratic Integer Programming Problem
Computational Optimization and Applications
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A bound is obtained in this note for the distance between the integer and real solutions to convex quadratic programs. This bound is a function of the condition number of the Hessian matrix. We further extend this proximity result to convex programs and mixed-integer convex programs. We also show that this bound is achievable in certain situations and the distance between the integer and continuous minimizers may tend to infinity.