About: Simulation Optimization Library: Throughput Maximization

The problem of Throughput Maximization is a family of iterative stochastic optimization algorithms that attempt to find the maximum expected throughput in an n-stage Flow line. According to Pichitlamken et al. (2006), there are two solutions to the discrete service-rate moderate-sized problem. With an expected throughput (defined as the limiting throughput over a long time horizon, as opposed to the approximation induced through the need for a warm-up period and ratio-estimate as described under . Each simulation replication should consist of warming up the system with 2000 released jobs starting from an empty system, then recording the time T required to release the next 50 jobs, and estimating the throughput on this replication as 50=T jobs per unit time. Time is then measured in the num