'PSA-SPN' - A Parameter Sensitivity Analysis Method Using Stochastic Petri Nets: Application to a Production Line System
- 1. EPMI-ECS, 13 Bld de l'Hautil, 95092 Cergy-Pontoise Cedex (France)
- 2. INRIA Rennes, DIONYSOS, Bretagne Atlantique, Campus Universitaire de Beaulieu, 35042 Rennes (France)
- 3. UTT-ICD, Universite de Technologie de Troyes, 12 rue Marie Curie, BP2060, 10010 Troyes (France)
Description
The dynamic behavior of a discrete event dynamic system can be significantly affected for some uncertain changes in its decision parameters. So, parameter sensitivity analysis would be a useful way in studying the effects of these changes on the system performance. In the past, the sensitivity analysis approaches are frequently based on simulation models. In recent years, formal methods based on stochastic process including Markov process are proposed in the literature. In this paper, we are interested in the parameter sensitivity analysis of discrete event dynamic systems by using stochastic Petri nets models as a tool for modelling and performance evaluation. A sensitivity analysis approach based on stochastic Petri nets, called PSA-SPN method, will be proposed with an application to a production line system.
Additional details
Identifiers
- DOI
- 10.1063/1.3106483;
Publishing Information
- Journal Title
- AIP Conference Proceedings
- Journal Volume
- 1107
- Journal Issue
- 1
- Journal Page Range
- p. 263-268
- ISSN
- 0094-243X
- CODEN
- APCPCS
Conference
- Title
- 2. Mediterranean conference on intelligent systems and automation
- Acronym
- CISA'09
- Dates
- 23-25 Mar 2009
- Place
- Zarzis (Tunisia)
INIS
- Country of Publication
- United States
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 41039322
- Subject category
- S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; S42: ENGINEERING;
- Resource subtype / Literary indicator
- Conference
- Descriptors DEI
- EVALUATION; MARKOV PROCESS; MATHEMATICAL MODELS; PERFORMANCE; SENSITIVITY ANALYSIS; SIMULATION; STOCHASTIC PROCESSES
- Descriptors DEC
- STOCHASTIC PROCESSES
Optional Information
- Notes
- (c) 2009 American Institute of Physics