Clustering-Assisted Preselection Multiobjective Optimization for Equipment Portfolio
Ningning Wang, Tingrui Liu, Xiangzhou Gao, Shenmin Song · 2024
The optimization of equipment system combination is crucial for the pre-deployment decision-making of our military. In order to obtain advantageous equipment portfolio solutions, we establish a multi-layer network optimization model for equipment systems and introduce a novel multi-objective optimization algorithm for equipment portfolios in combat systems. Firstly, a multi-objective optimization model for equipment system combination recommendation is established, with the objective of optimizing combat network redundancy and vulnerability. Secondly, due to the complexity of the equipment system optimization model and the challenge of finding optimal equipment portfolios, we propose a clustering-assisted preselection multi-objective evolutionary algorithm called MECAP. This algorithm is designed to enhance the convergence of the population towards the optimal solution set. Additionally, the experimental results highlight the benefits of applying MECAP for offspring generation strategy after model sampling.