WaitTimeSimkit

This application is based on the classic M/M/c/K model of queuing theory, providing users with a one-stop solution for queue performance analysis. By inputting the average arrival rate (λ), average service rate (μ), number of service desks (c), and system capacity (K), the following key indicators can be quickly calculated:
System full probability (P_K): The probability that the system is full when customers arrive, reflecting the level of service resource tension;
Effective arrival rate (λ _ eff): Consider the actual rate at which customers enter the system after refusing to queue;
Average team leader (L) and queue leader (Lq): The total number of customers in the system and the average number of people waiting in line;
Average Stay Time (W) and Waiting Time (Wq): The average time spent by customers in the system and their queue time;
Customer loss rate: The proportion of customers who are rejected due to the system being fully staffed, directly related to service experience and revenue.