Journal of the Korea Society for Simulation (한국시뮬레이션학회논문지)

The Korea Society for Simulation (한국시뮬레이션학회)
권호 표지

Optimization of Queueing Network by Perturbation Analysis

퍼터베이션 분석을 이용한 대기행렬 네트워크의 최적화

  • Published : 2000.06.01
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, we consider an optimal allocation of constant service efforts in queueing network to maximize the system throughput. For this purpose, 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.

Keywords

References

  1. J. of the Operational Research Society v.44 Simulation and Queueing Theory Applied to a Single -Server Queue with Advertising and Balking Ackere. A.V;P. Ninios
  2. Proceedings of the WSC A New Algorithm for Stochastic Optimization Andradottir. S
  3. handbook of Simulation Principle Methodology, Advance, Applications and Practice Simulation Optimization Andradottir. S
  4. J. of the Operational Research society v.47 A note on a Queueing Optimization Problem Atkinson. J.B;J. Banks.(ed)
  5. Proceedings of the WSC Application of Perturbation Analysis to (s, S)Inventory Systems Bashynam. S;M.C. Fu
  6. Proceedings of the WSC Simulation Optimization Methods and Applications Carson. Y;A. Maria
  7. SIAM J., v.31 no.3 Optimization of Queues Using Infinitesmal Perturbation Analysis-Based Stochastic Algorithm with General Update Times Chong. E.K.P;P. Ramadge
  8. IEEE transactions on Automatic Control v.36 no.8 On Sampling controlled Stochastic Approximation Dupis. P;R. Simha
  9. Management Science v.40 no.10 Stochastic Optimization by Simulation : Numerical Experiments with the M/M/1 Queue in Steady-state Ecuyer P.L.;N. Giroux;P.W. Glynn
  10. Management Science v.40 no.11 Stochastic Optimization by Simulation : Convergence Proofs for the GI/G/1 Queue in Steady -state Ecuyer. P.L;P.W. Glynn
  11. Management Science v.41 no.2 Sensitivity Analysis for Base-stock Levels in Multiechelon Production-inventory Systems Glasserman. P;S. Tayur
  12. Journal of Optimization Theory and Applications v.40 no.4 Perturbation Analysis and Optimization of Queueing Networks Ho. Y.C;Cao. X
  13. Pertubation Analysis of Discrete Event Dynamic Systems Ho. Y.C;Cao. X
  14. J. of the Operational Research Society v.45 Queueing Models for Optimizing System Availability of a Flexible Manufacturing System Lin. C;C. Madu;T.W. Chien;C. Kuei
  15. Flexible Assembly Systems Owen. A.E
  16. Annal of Mathematical Statistics v.22 A Stochastic Approximation Method Robbins. H;S. Monro
  17. Journal of Optimization Theory and Applications v.40 no.4 Implementation of Sensitivity Calculations on a Monte Carlo Experiment Suri. R