Weapon systems portfolio selection based on fuzzy clustering analysis

In the modern joint war, the weapon systems portfolio selection is a necessary procedure for military development and research. The research on weapon system portfolio selection has made some achievements. Generally, the multi-objective programming methods and some intelligent algorithms are used to solve the problem. In this paper, the fuzzy clustering analysis and the maximum deviation methods are applied to get the weapon systems portfolio selection problem by ranking all the candidate and calculating the weight of each weapon system in the composition. In the process of making portfolio selection, the factors that affect the final performance of weapon systems and the cost are widely considered. Finally, a case is studied to illustrate the usefulness and efficiency of the proposed method and model.