  We introduce a new technique for solving uni-parametric versions of linear
programs, convex quadratic programs, and linear complementarity problems in
which a single parameter is permitted to be present in any of the input data.
We demonstrate the use of our method on a small, motivating example and present
the results of a small number of computational tests demonstrating its utility
for larger scale problems.
