In the process of traditional weapon-target assignment, there are two critical issues that have not been well-studied: (1) the waste of firepower resources and (2) the lack of description of the relationship between targets. Towards this end, we propose an improved weapon-target assignment model, which combines the damage probability, the weapon resource consumption and the relationship coefficient between the targets. On this basic, we design a multi-objective whale optimization algorithm based on grid division (GDMOWOA). Specifically, the algorithm uses the grid partitioning method to sort the population non-dominated, selects the optimal individual by calculating the grid number and density, and introduces an external Pareto archive to maintain the population diversity. Simulation experiments are conducted to verify the rationality and effectiveness of our solution. The results show that our algorithm has better effectiveness and superiority compared with other classical algorithms, and can effectively solve the problem of weapon-target assignment.
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