Performance Evaluation of Stochastic Systems: Discretization and Decomposition
(2012) ILS′2012 : International Conference on Information Systems, Logistics and Supply Chain — Location: Québec, Canada (26.August.2012)
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- Abstract
- The performance evaluation of stochastic production systems is crucial to support managers decisions as well as challenging for researchers. In this paper, we propose a new methodology to analyze production systems with general assumptions : assembly/disassembly systems, general processing time distributions and finite storages spaces. The general distributions are first discretized by probability mass fitting, and the transformed system is then analytically modelled by decomposition. The system is decomposed into two station subsystems and the processing time distributions of the virtual stations are iteratively modified to approximate the impact of the rest of the network, adding estimations of the blocking and starving distributions. Decomposition allows to analyze large systems in a reasonable computational time (unlike exact models), and with good accuracy. Computational experiments show that the relative error is on the order of one percent, and less with buffer sizes larger than two. Moreover, as it allows a fine approximation of the blocking and starving time distributions, PMF seems to bring an improvement in the application of the decomposition technique.
- Affiliations
Louvain School of Management Operations and Information FUCaM Sciences de gestion
Citations
Tancrez, J.-S. (2012). Performance Evaluation of Stochastic Systems: Discretization and Decomposition. ILS′2012 : International Conference on Information Systems, Logistics and Supply Chain, Québec, Canada. https://hdl.handle.net/2078.5/250574