Uncertainty on Discrete-Event System Simulation

2022 ◽  
Vol 32 (1) ◽  
pp. 1-27
Author(s):  
Damian Vicino ◽  
Gabriel A. Wainer ◽  
Olivier Dalle
Keyword(s):  
Dynamic Systems ◽  
Discrete Event ◽  
Discrete Event System ◽  
Discrete Event Dynamic Systems ◽  
Computable Model ◽  
Continuous Variables ◽  
System Specification ◽  
Model Approximation ◽  
Discrete Event System Specification ◽  
Event System

Uncertainty Propagation methods are well-established when used in modeling and simulation formalisms like differential equations. Nevertheless, until now there are no methods for Discrete-Dynamic Systems. Uncertainty-Aware Discrete-Event System Specification (UA-DEVS) is a formalism for modeling Discrete-Event Dynamic Systems that include uncertainty quantification in messages, states, and event times. UA-DEVS models provide a theoretical framework to describe the models’ uncertainty and their properties. As UA-DEVS models can include continuous variables and non-computable functions, their simulation could be non-computable. For this reason, we also introduce Interval-Approximated Discrete-Event System Specification (IA-DEVS), a formalism that approximates UA-DEVS models using a set of order and bounding functions to obtain a computable model. The computable model approximation produces a tree of all trajectories that can be traversed from the original model and some erroneous ones introduced by the approximation process. We also introduce abstract simulation algorithms for IA-DEVS, present a case study of UA-DEVS, its IA-DEVS approximation and, its simulation results using the algorithms defined.

scholarly journals A DSDEVS-Based Model for Verifying Structural Constraints in Dynamic Business Processes

2020 ◽  
Vol 44 (2) ◽  
pp. 257-273
Author(s):  
Sofiane Boukelkoul ◽  
Ramdane Maamri
Keyword(s):  
Business Processes ◽  
Discrete Event ◽  
Dynamic Structure ◽  
Discrete Event System ◽  
Structural Constraints ◽  
System Specification ◽  
Discrete Event System Specification ◽  
Event System ◽  
Proposed Model ◽  
Structure Properties

This paper presents a DSDEVS-based model “Dynamic Structure Discrete Event System specification” for modeling and simulating business processes with dynamic structure regarding to different contexts. Consequently, this model, formally, improves the reuse of configurable business processes. Thus, the proposed model allows the analysts to personalize their configurable business processes in a sound manner by verifying a set of structure properties, such as, the lack of synchronization and the deadlock by means of simulation. The implementation was done in DEVS-Suite simulator, which is based on DEVSJAVA models.

scholarly journals Modeling and simulation of oncology clinic operations in discrete event system specification

SIMULATION ◽  
2017 ◽  
Vol 94 (2) ◽  
pp. 105-121 ◽  
Author(s):  
Michelle M Alvarado ◽  
Tanisha G Cotton ◽  
Lewis Ntaimo ◽  
Eduardo Pérez ◽  
William R Carpentier
Keyword(s):  
Operations Management ◽  
Discrete Event ◽  
Treatment Method ◽  
Discrete Event System ◽  
Arrival Process ◽  
System Specification ◽  
Operation Performance ◽  
Discrete Event System Specification ◽  
Event System ◽  
Chemotherapy Patients

Oncology clinics are often burdened with scheduling large volumes of cancer patients for chemotherapy under limited resources, such as nurses and chemotherapy chairs. Chemotherapy is a cancer treatment method that is administered orally or intravenously at an outpatient oncology clinic. Chemotherapy patients require a treatment regimen, which is a series of appointments over several weeks or months prescribed by the oncologist. The timing of these appointments is critical to the effectiveness of the chemotherapy treatment on cancer. This motivates the need for new methods for making efficient appointment schedules and for assessing clinic operation performance from both patient and management perspectives. This work uses a classic modeling approach based on systems theory to develop a discrete event system specification (DEVS) simulation model for oncology clinic operations called DEVS-CHEMO. DEVS-CHEMO is configurable to any oncology clinic and provides several capabilities for oncology clinic managers. For example, it can simulate scheduling of chemotherapy patients, clinic resources, and the arrival process of the patients to the clinic on the day of their appointment. This model simulates oncology clinic operations as patients receive chemotherapy treatments and thus allows for assessing scheduling algorithms using both patient and management perspectives. DEVS-CHEMO has been tested and validated using historical data from a real outpatient oncology clinic and the simulation results reported in this paper provide several insights regarding oncology clinic operations management.

Configuration space–based discrete event system specification formalism for a smart factory with real-time flexibility

2018 ◽  
Vol 26 (3) ◽  
pp. 265-275 ◽  
Author(s):  
Dae S Chang ◽  
Sang C Park
Keyword(s):  
Real Time ◽  
Configuration Space ◽  
Manufacturing Systems ◽  
Discrete Event ◽  
Discrete Event System ◽  
Smart Factory ◽  
System Specification ◽  
Discrete Event System Specification ◽  
Event System ◽  
Effective Description

A manufacturing system consists of various manufacturing devices, and each device has a set of tasks which are triggered by specific commands. Traditionally, simulation has been considered as an essential technology for the evaluation and analysis of manufacturing systems. Although discrete event system specification formalism has been a popular modeling tool for manufacturing systems, it has limitations in describing situations such as sudden cancelation of tasks. Proposed in this article is an extended discrete event system specification formalism for the effective description of a smart factory which requires the intelligence to handle turbulences in real-time production. The extended discrete event system specification formalism incorporates the configuration space concept, which is well-known in classical mechanics. While the conventional discrete event system specification formalism uses only the logical states set to represent the device states, the proposed formalism employs the combination of two sets: a logical states set (sequential states set) and a physical states set (configuration space of the device). As a result, the extended formalism enables the effective description of nondeterministic tasks which may occur frequently in a smart factory.

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