Simple Computable Bounds for Solutions of Linear Complementarity Problems and Linear Programs.
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WISCONSIN UNIV-MADISON MATHEMATICS RESEARCH CENTER
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Surprisingly simple bounds are given for solutions of fundamental constrained optimization problems such as linear and convex quadratic programs. It is shown that every nonoptimal primal-dual feasible point carries within it simple numerical information which bounds some or all components of all solution vectors. The results given permit one to compute bounds without even solving the optimization problems. Author
- Theoretical Mathematics