A Dynamic Greedy Heuristic for Scheduling Training Scenarios.
Master's thesis, Aug 95-May 97,
UNIVERSITY OF CENTRAL FLORIDA ORLANDO
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The current approach for CCTTClose Combat Tactical Trainer scheduling considers only one resource constraint semi-automated computer generated forces SAF. Use of this approach can result in an infeasible schedule being produced because it only considers total SAF and to the resulting schedule exceeds the capacity for manned simulator modules as well as other limited resources. In selecting scenarios for training units may choose from several alternatives, all of which may support a desired set of training objectives. It is assumed that the objective of the schedule maximizing resource utilization, would be highly desired by military leaders and managers of the CCTT system. Therefore, a greedy heuristic approach is used to solve the multi-stage scheduling decision process. The problem was formulated using a zero-one integer program where the algorithm minimizes slack resources at each stage of the scheduling process subject to local and temporal constraints. Stage times are defined as scenario completion times. By minimizing slack resources, resource utilization is maximized. Results generated by the algorithm developed in this thesis were both feasible and efficient, in all cases. resource constraints and all precedence relationships were satisfied. Key resources simulators, and SAF work stations had utilization percentages ranging from 69 to 92.
- Computer Programming and Software
- Military Operations, Strategy and Tactics