A finiteness proof for modified dantzig cuts in integer programming

Let \documentclass{article}\pagestyle{empty}\begin{document}$$ x_i = y_{i0} - \sum\limits_{j \in R} {y_{ij} x_j, i = 0},...,m $$\end{document} be a basic solution to the linear programming problem \documentclass{article}\pagestyle{empty}\begin{document}$$ \max \,x_0 = \sum {{}_jc_j x_j } $$\end{document} subject to: \documentclass{article}\pagestyle{empty}\begin{document}$$ \sum {{}_ja_{ij} x_j } = b_i, i=1,...,m, $$\end{document} where R is the index set associated with the nonbasic variables. If all of the variables are constrained to be nonnegative integers and xu is not an integer in the basic solution, the linear constraint \documentclass{article}\pagestyle{empty}\begin{document}$$\sum\limits_{j \in R_u^* } {x_j \ge 1,} \,R_u^* = \{ j|j \in R\,{\rm\, and}\,\,y_{uj} \ne {\rm integer}\}$$\end{document} is implied. We prove that including these “cuts” in a specified way yields a finite dual simplex algorithm for the pure integer programming problem. The relation of these modified Dantzig cuts to Gomory cuts is discussed.