Dynamic optimization model of weapon equipment system effectiveness based on A-GERT network

Abstract

Aiming at the difficulties in system modeling and quantification of system effectiveness in system optimization, this paper, based on an in-depth analysis of the weapon equipment architecture, constructs a system AGERT network with a self-learning mechanism through agent-based modeling and graphical evaluation and review technique (GERT) to achieve system effectiveness optimization. Secondly, based on the moment generating function and the Mersenne formula, the calculation method and proof of the success probability and combat effectiveness of the system combat chain/network mission are given. Based on a profound analysis of the contribution of the system components, the expected contribution evaluation model of the system components based on the Shapley value is proposed with the help of the idea of fair distribution of benefits in cooperative gaming. Then, based on the Markov process theory, the A-GERT network system effectiveness optimization algorithm based on the contribution of the components is proposed. Finally, combined with a case study, the feasibility and effectiveness of the proposed model are demonstrated.