Research on Modeling and Optimization Methods for the Weapon-Target Allocation Problem

With the increasing complexity of modern warfare and the growing demand for multi-objective optimization, the Weapon-Target Allocation (WTA) problem has become a crucial research topic in military strategy. This paper focuses on modeling and optimizing the WTA problem in multi-round strike scenarios and proposes a solution that combines multi-objective optimization with an improved simulated annealing algorithm. The model aims to minimize the total base damage while maximizing the target interception rate, employing the weighted sum method to balance conflicting objectives. Additionally, a dynamic neighborhood search mechanism is introduced to enhance the simulated annealing algorithm, improving the efficiency of global optimal solution search. Experimental results demonstrate that the improved algorithm outperforms traditional methods in both computation time and base protection levels, providing effective support for defense decision-making in complex and dynamic battlefield environments.