Recently, the shared use of mobile tools has been expanding, such as bicycles being provided in areas designated for rental bicycles. However, concentrating mobile tools at a node is a critical issue. To resolve this problem, we use a closed queuing network to calculate the average standby number and average waiting time for the mobile tools at each node, and then select an optimal node from among the candidate nodes. As the model itself assumes stationarity for optimal node placement using the

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... closed queuing network, characteristic quantities are obtained after sufficient time has passed. User trends are fluctuating, and in many cases, the trends cannot be considered using only basic statistics such as averaging. Hence, we simulate this model for optimal node placement in a closed queuing network and obtain detailed information along the time series as information that can correspond to the actual model. To demonstrate applicability to the actual model, we chose Hamanako Garden Park. We installed some mobile tools in the park and evaluated the distribution of the tools when used by visitors. The information obtained from this simulation includes the percentage of time when there is no mobile tool at the node, the percentage of time of node overcapacity, and the degree of influence on the increase and decrease in the number of mobile tools at each node. We propose a new optimal node placement platform by linking the simulation to optimal node placement using the closed queuing network proposed, and expect that it will be applicable to a wide range of models.