John McDonnell, Nick Gizzi
Space and Naval Warfare Systems Center
53560 Hull Street
San Diego, CA 92152
mcdonn, gizzi@spawar.navy.mil
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Sushil J. Louis
Genetic Algorithm Systems Laboratory
Department of Computer Science
University of Nevada, Reno
sushil@cs.unr.edu
We investigate the problem of allocating strike force assets in a dynamic targetting environment using a genetic algorithm. The nonlinear programming formulation developed in this paper encompasses both strike and suppression responsibilities as well as multi-target and multi-threat allocations. Partitioning the allocation strategy matrix into strike and suppression components results in a more effective search. Results on two constructed problems show that the genetic algorithm quickly and reliably finds optimal or near-optimal allocations.
Keywords: Asset Allocation, Genetic Algorithms