Some Linear Programming Applications to Stockage Problems

by Robin B. S. Brooks


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The use of linear programming algorithms for solving Air Force stockage problems such as the following: design of a mobility kit of reparables; single multi-weapon base stockage of reparables, recoverables and war reserve supplements, and EOQ items; and multi-echelon multi-base stockage of recoverable items with and without additional procurement. The decision variables in the last-named case are depot stock levels for each item, base stock levels for each item for each base, and procurement for each item; the policy characteristics are total additional procurement cost, amount of support given the bases, and, for each item, the amount by which procurement plus assets falls short of the sum of base and depot levels. Instead of attempting exact solutions to the problems considered in the study, a procedure is suggested that will provide approximate solutions. It is "fail safe" in the sense that if the policies computed are good approximations to one another, then any of them provides a good approximation to the solution. Since the number of decision variables is large compared with the number of policy characteristics, the standard simplex method is impractical because of the large number of vectors to be enumerated. It is more feasible to solve by the simplex method using multipliers.

This report is part of the RAND Corporation Research memorandum series. The Research Memorandum was a product of the RAND Corporation from 1948 to 1973 that represented working papers meant to report current results of RAND research to appropriate audiences.

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