Optimal Multi-stage Allocation of Weapons to Targets Using Adaptive Dynamic Programming
We consider the optimal allocation of resources (weapons) to a collection of tasks (targets) with the objective of maximizing the reward for completing tasks (destroying targets). Tasks arrive in two stages, where the first stage tasks are known and the second stage task arrivals follow a random distribution. Given the distribution of these second stage task arrivals, simulation and mathematical programming are used within a dynamic programming framework to determine optimal allocation strategies. The special structure of the assignment problem is exploited to recursively update functional approximations representing future rewards using subgradient information. Through several theorems, optimality of the algorithm is proven for a two-stage Dynamic Weapon-Target Assignment Problem.
Ahner, D.K., Parson, C.R. Optimal multi-stage allocation of weapons to targets using adaptive dynamic programming. Optim Lett 9, 1689–1701 (2015). https://doi.org/10.1007/s11590-014-0823-x
The "Link to Full Text" button on this page loads the journal article hosted at the publisher’s website. Provided by the Springer Nature SharedIt content sharing program. Please attribute the work using the citation indicated below.
Copyright statement: © Springer-Verlag Berlin Heidelberg (outside the USA) 2014