Self-adaptive learning based discrete differential evolution algorithm for solving CJWTA problem

Cooperative jamming weapon-target assignment (CJWTA) problem is a key issue in electronic countermeasures (ECM). Some symbols which relevant to the CJWTA are defined firstly. Then, a formulation of jamming fitness is presented. Finally, a model of the CJWTA problem is constructed. In order to solve the CJWTA problem efficiently, a self-adaptive learning based discrete differential evolution (SLDDE) algorithm is proposed by introducing a self-adaptive learning mechanism into the traditional discrete differential evolution algorithm. The SLDDE algorithm steers four candidate solution generation strategies simultaneously in the framework of the self-adaptive learning mechanism. Computational simulations are conducted on ten test instances of CJWTA problem. The experimental results demonstrate that the proposed SLDDE algorithm not only can generate better results than only one strategy based discrete differential algorithms, but also outperforms two algorithms which are proposed recently for the weapon-target assignment problems.