In this paper, we consider an optimal allocation of constant service efforts in queueing network to maximize the system throughput. For this pose, using the perturbation analysis, we apply a stochastic optimization algorithm to two types of queueing systems. Our simulation results indicate that the estimates obtained from a stochastic optimization algorithm for a two-tandem queuing network are very accurate, and those for closed loop manufacturing system are a little apart from the known optimal allocation. We find that as simulation time increases for obtaining a new gradient (performance measure with respect to decision variables) by perturbation algorithm, the estimates tend to be more stable. Thus, we consider that it would be more desirable to have more accurate sensitivity of performance measure by enlarging simulation time rather than more searching steps with less accurate sensitivity. We realize that more experiments on various types of systems are needed to identify such a relationship with regards to stopping rule, the size of moving step, and updating period for sensitivity.
1. Introduction
2. Perturbation Analysis
3. Stochastic Optimization Algorithm
4. Numerical Example
5. Conclusion
References