Accession Number : ADA311115
Title : Stochastic Set Partitioning Methods for Operational Planning of Aircraft and Crews.
Descriptive Note : Final rept. 1 Sep 92-31 Aug 95,
Corporate Author : PRINCETON UNIV NJ DEPT OF CIVIL ENGINEERING AND OPERATIONS RESEARCH
Personal Author(s) : Powell, Warren B.
PDF Url : ADA311115
Report Date : 08 MAY 1996
Pagination or Media Count : 10
Abstract : The project is developing control technologies for large, complex operational problems. These technologies are intended for both real time and tactical planning, and can be imbedded in larger simulation models for strategic planning purposes. In a simulation setting. the techniques provide' optimization capabilities within strategic planning models, replacing the simple rules and heuristics most commonly used in simulation models. By contrast, they offer much more flexibility than classical linear programming models. In a real time setting, the optimization methods provide tremendous flexibility and fast response with relatively easy diagnostics. The tools are especially robust with respect to the uncertainties that are intrinsic to any real time setting. In addition to the development of new optimization techniques, the research encompasses heuristic learning, graphical diagnostics, a modular object library, and a flexible simulation architecture that can be used to test and evaluate different optimization techniques, as well as perform detailed simulations for strategic planning purposes.
Descriptors : *FLIGHT CREWS, *OPERATIONS RESEARCH, *MILITARY PLANNING, SIMULATION, METHODOLOGY, QUICK REACTION, OPTIMIZATION, STOCHASTIC PROCESSES, STRATEGIC ANALYSIS, REAL TIME, GRAPHICS, DIAGNOSIS(GENERAL), HEURISTIC METHODS, CONTROL THEORY, LEARNING.
Subject Categories : Operations Research
Distribution Statement : APPROVED FOR PUBLIC RELEASE