Research on Supermarket Customer Classification Based on Agent Ant Colony Algorithm

The Ant colony algorithm is an intelligent algorithm with its better robustness and parallelism, as well as the advantage combined easily with other algorithms. Each ant Agent does not need to have a comprehensive understanding to the every aspect of the system so the individual Agent is considered as the main object of study. In the paper, supermarket customer subdivision model was researched by the self organizational peculiarity of ant colony algorithm and the intelligent advantage of Agent, which not only embodied the principle of simplicity but also achieved better customer subdivision results. Considering the peculiarities of supermarket customers, ant colony algorithm was combined with Agent, which was applied to research of supermarket customer subdivision model. Adopting the Repast J simulation platform, the process and results of simulation were more intuitive. The results show that the algorithm has the better validity and stability and can provide more effective support for decision-making of governor in the area of supermarket customer management.