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A Digital Assorting System (DAS) is a logistics system to assort the products in distribution centers that handle fresh products. High levels of productivity to maintain their freshness are required for a distribution center. We developed two discrete event simulation models to evaluate productivity that are person-following robotic carts based DAS and worker-based DAS. Besides, we conducted simulation experiments by setting several scenarios for checking the factors such as the number of products, product popularity, the capacity and number of people-following robot carts, and speed. As a result, we confirmed that decision-makers should consider several factors such as system layouts, the size of products, and the waiting time caused by blocking among the people-following robot carts to outperform the existing DAS.