Postoptimality Analysis II

Abstract

In the preceding chapter we considered, in part, an assortment of postoptimality problems involving discrete changes in only selected components of the matrices C, b, or A. Therein emphasis was placed upon the extent to which a given problem may be modified without breaching its feasibility or optimality. We now wish to extend this sensitivity analysis a bit further to what is called parametric analysis. That is, instead of just determining the amount by which a few individual components of the aforementioned matrices may be altered in some particular way before the feasibility or optimality of the current solution is violated, let us generate a sequence of basic solutions which in turn become optimal, one after the other, as all of the components of C, b, or a column of A vary continuously in some prescribed direction. In this regard, the following parametric analysis will involve a marriage between sensitivity analysis and simplex pivoting.