On the 100% rule of sensitivity analysis in linear programming
The 100% Rule was introduced by Bradley, Hax and Magnanti  in Sensitivity Analysis of linear programming theory. It is concerned with the qualitative behavior of an optimal solution as it changes according to the right hand side vector. We extend this 100% Rule to the most generalized form, to deal with changes in all the parameters of any given linear program, including the coefficients of the matrix, the objective function as well as the right hand side vector.
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