Machine learning-based evolution model and the simulation of a profit model of agricultural products logistics financing

Abstract

An agricultural products logistics and financial warehousing business mainly involves a tripartite of agricultural production and processing enterprises, third-party logistics enterprises and financial institutions and enables the three parties to achieve win–win outcomes. This article first identifies the dynamic and evolutionary stability strategies used by the businesses participating in the tripartite and then uses the NetLogo simulation platform and the multi-agent modelling and simulation method to establish an asymmetric evolutionary game simulation model that allows for the participation of the three parties; this study runs the model under different revenue parameters. Finally, this study analyses the behaviour of asymmetric cooperative competition games in the process of selecting different strategies and identifies strategies that should be used by nonsymmetric member companies that cooperate. To manage the logistics of agricultural products, financial financing businesses participate in the tripartite and obtain mutually beneficial win–win outcomes, thus promoting the smooth development of agricultural logistics businesses and ensuring the cooperation between agricultural production and processing enterprises and third-party logistics enterprises so they can realize common development.