RECAL—a new efficient algorithm for the exact analysis of multiple-chain closed queuing networks
Journal of the ACM (JACM)
Mean Value Analysis by Chain of Product form Queueing Networks
IEEE Transactions on Computers
Performance analysis of scheduling policies in re-entrant manufacturing systems
Computers and Operations Research
Stability and instability of fluid models for reentrant lines
Mathematics of Operations Research
Analytical Performance Modeling of Hierarchical Mass Storage Systems
IEEE Transactions on Computers
Robust bounds and throughput guarantees for closed multiclass queueing networks
Performance Evaluation
Mean-Value Analysis of Closed Multichain Queuing Networks
Journal of the ACM (JACM)
Computers and Operations Research
Performance analysis in a probabilistic re-entrant for an environmental stress testing operation
Computers and Industrial Engineering
Computers and Operations Research
Modeling and simulation of a re-entrant manufacturing system using Colored Petri Nets
Proceedings of the 45th Annual Simulation Symposium
An MVA approximation for conwip priority modeling
Proceedings of the Winter Simulation Conference
Hi-index | 0.01 |
We propose an approximate approach for estimating the performance measures of the re-entrant line with single-job machines and batch machines based on the mean value analysis (MVA) technique. Multi-class jobs are assumed to be processed in predetermined routings, in which some processes may utilize the same machines in the re-entrant fashion. The performance measures of interest are the steady-state averages of the cycle time of each job class, the queue length of each buffer, and the throughput of the system. The system may not be modeled by a product form queueing network due to the inclusion of the batch machines and the multi-class jobs with different processing times. Thus, we present a methodology for approximately analyzing such a re-entrant line using the iterative procedures based upon the MVA and some heuristic adjustments. Numerical experiments show that the relative errors of the proposed method are within 5% as compared against the simulation results.