The invention discloses a multi-target weapon-
target distribution method based on an artificial fish swarm
algorithm, aiming to overcome the defect that solving for a WTA problem in the prior art deviates from a real Pareto
leading edge greatly. The multi-target weapon-
target distribution method comprises the following steps: firstly, randomly generating an initial
population, calculating a non-dominated solution set of the initial
population, and sorting according to a congestion distance to obtain a globally optimal solution of the initial
population; then, according to the clustering behavior of the artificial fish swarm
algorithm, enabling other individual fishes in the fish swarm to approach the optimal solution to obtain a
new population and a previous non-dominated solution set, andcalculating a new non-dominated solution set; and finally, carrying out
crossover variation on the clustered population to increase
population diversity, combining with the previous non-dominated solution set again, and carrying out multiple iterations to obtain a final Pareto
leading edge. The multi-target weapon-
target distribution method is mainly used in the field of fire fighting
decision making, is closer to the real Pareto frontier compared with the prior art, has small dependence on parameters, and has great application value in multi-target weapon-target distribution.