Abstract
For some specified targets, it is desired to identify the optimal configuration for the assignment of weapons for a given deployment of different types of weapon systems along with their required quantity in order to achieve a desired level of damage subject to the minimal cost and mission specific constraints. This problem, in its essence, is an NP-complete combinatorial optimization problem in the area of command and control research. In defense-related applications of artificial intelligence, this problem is referred as Weapon Target Assignment (WTA) problem. The problem can be formulated as a non-linear integer programming problem for which no exact methods exist to solve even the small size instances. Our focus is on the Dynamic Weapon Target Assignment (DWTA) problem. A discrete-event system simulation model is developed taking into account the resource constraints, resource capability constraints, strategy constraints and engagement feasibility constraints. Three different methods are employed; MMR, Reactive Tabu Search and a newly proposed artificial intelligence based simulation-optimization hybrid framework. A set of rules is generated based on the optimization module that is then employed for real-time control. The computational results show very promising prospects of the proposed approach, not only for DWTA but also for any real-time decision-making problem like Cooperative Unmanned Air Vehicle Mission Assignment etc.