Title :
MAAP: the military aircraft allocation planner
Author :
Abrahams, P. ; Balart, R. ; Byrnes, J.S. ; Cochran, D. ; Larkin, M.J. ; Moran, W. ; Ostheimer, G. ; Pollington, A.
Author_Institution :
Prometheus Inc., Newport, RI, USA
Abstract :
The authors present an application of genetic algorithms to the field of large-scale allocation problems in which a collection of resources (assets) must be mapped in an optimal or near-optimal manner to a number of objectives (targets), as measured by an objective function. Such problems are complex due to their requirements for integer solutions, non-linear objective functions and linear asset constraints. Genetic algorithms have turned out to be a natural fit for this application. They summarize the scope of the MAAP tool prototype as delivered to the U.S. Air Force and indicate their plans for ongoing and future research
Keywords :
genetic algorithms; military aircraft; planning; resource allocation; MAAP; US Air Force; genetic algorithm; integer solutions; large-scale allocation problems; linear asset constraints; military aircraft allocation planner; nonlinear objective functions; objective function; resources; Air traffic control; Asset management; Costs; Genetic algorithms; Large-scale systems; Military aircraft; Prototypes; Resource management; Software tools; Testing;
Conference_Titel :
Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4869-9
DOI :
10.1109/ICEC.1998.699755