The Stochastic Generalized Transportation Problem -- An Operator Theoretic Approach.
CARNEGIE-MELLON UNIV PITTSBURGH PA MANAGEMENT SCIENCES RESEARCH GROUP
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The paper investigates the Stochastic Generalized Transportation Problem with recourse when the demands column totals are random. The basic philosophy and assumptions are those of the two-stage linear programming under uncertainty. It is shown that the problem can be converted to an equivalent convex program where the random components are explicitly addressed in the functional thus retaining the dimensionality of the constraints unchanged. Utilizing Kuhn-Tucker conditions certain qualitative propositions and theorems are proved. These results lead to an efficient computer code which proceeds in an iterative process solving once the deterministic generalized transportation problem. Modified author abstract
- Operations Research