DocumentCode
326327
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
fYear
1998
fDate
4-9 May 1998
Firstpage
336
Lastpage
341
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/ICEC.1998.699755
Filename
699755
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