The Singularly Constrained Genera . Lized Network

This paper presents a computationally efficient method for solving generalized network problems with an additional linear constraint. The method is basically the primal simplex method specialized to exploit the topological structure of the problem. The method is similar to the specialization of Charnes and Cooper's Double Reverse Method by Meier, and Klingman and Russell for constrained pure network Problems. It couples the augmented predecessor index method with a double pricing procedure to yield an "inverse compactification" which reduces the arithmetic calculations required in pivoting. We also show, how to simplify and accelerate the steps of updating costs and finding basis representations by taking advantage of the quasi-triangularity of a basis.