Our approach to determining the design parameters for a multi- echelon maintenance system is to achieve a minimum-cost ar chitecture that delivers a specified level of availability to the sup port system. Decision variables represent the amount of test equipment and the number of spares allocated to the various repair levels. Structured as an optimization problem, the system performance measure is obtained through simulation. A direct search technique is employed to iteratively seek an indicated optimal solution. An additional decision criterion is used to deter mine the run length at each search point and for indicating termination.
Biles, W.E. "Experimental Design in Computer Simulation." Proceedings of the Winter Simulation Conference. IEEE, New York, N.Y. (1979), 3-9
2.
Biles, W.E. and Swain, J.J. "Mathematical Programming and the Optimization of Computer Simulations ." Mathematical Programming Study 11. North- Holland Publishing, New York, N.Y. ( 1979).
3.
Coughlin, R.J. "Optimization of Spares for Hardware Systems in a Complex Maintenance Scenario." Master's thesis, University of South Florida, Tampa, Fla. (1984 ).
4.
Drezner, S.M. and Hillestad, R.J. "Logistics Models: Evolution and Future Trends." In Military Modeling ( W.P. Hughes, ed.). Military Operations Research Society, Inc., Washington, D.C. (1984), 203-224.
5.
Matalon, E.A. "Systems Optimization Through Simulation." Master's thesis, Virginia Poly-technic Institute and State University , Blacksburg, Va. (1982).
6.
O'Malley, T.J.'The Aircraft Availability Model: Conceptual Framework and Mathematics." Technical report. Logistics Management Institute, Arlington, Va. ( 1983).
7.
Singh, N. and Vrat, P.'A Location-Allocation Model for a Two-Echelon Repair- Inventory System." IIE Transactions16:3 (1984), 222-228.
