Accession Number : ADA324239
Title : A Dynamic Greedy Heuristic for Scheduling Training Scenarios.
Descriptive Note : Master's thesis, Aug 95-May 97,
Corporate Author : UNIVERSITY OF CENTRAL FLORIDA ORLANDO
Personal Author(s) : Petit, Ray, Jr
PDF Url : ADA324239
Report Date : 1997
Pagination or Media Count : 156
Abstract : The current approach for CCTT(Close 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%.
Descriptors : *COMPUTERIZED SIMULATION, *TRAINING DEVICES, *TACTICAL WARFARE, ALGORITHMS, SCENARIOS, ARMY TRAINING, CLOSE SUPPORT, COMBAT SUPPORT, INTEGER PROGRAMMING, SCHEDULING, HEURISTIC METHODS, RESOURCES, MILITARY COMMANDERS, UTILIZATION.
Subject Categories : Computer Programming and Software
Military Operations, Strategy and Tactics
Distribution Statement : APPROVED FOR PUBLIC RELEASE