Shuffled Frog Leaping Algorithm with Non-Dominated Sorting for Dynamic Weapon-Target Assignment

The dynamic weapon target assignment (DWTA) problem is of great significance in modern air combat. However, DWTA a highly complex constrained multi-objective combinatorial optimization problem. An improved elitist non-dominated sorting genetic algorithm-II (NSGA-II) called the shuffled frog leaping algorithm (NSFLA) proposed to maximize damage enemy targets and minimize self-threat combat constraints. In NSFLA, (SFLA) introduced NSGA-II replace inside evolutionary scheme (GA), displaying low speed heterogeneous space search defects. Two improvements have also been raised promote internal performance SFLA. Firstly, local evolution scheme, novel crossover mechanism, ensures that each individual participates updating instead only worst ones, which can expand diversity population. Secondly, discrete adaptive mutation based on function change rate applied balance global search. Finally, verified various scenarios. results show NSFLA has apparent advantages solution quality efficiency, especially many aircraft environment.