Journal articles: 'Discrete-Event System Simulation Approach'

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Flood, Ian, and Kenneth Worley. "An artificial neural network approach to discrete-event simulation." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 9, no. 1 (January 1995): 37–49. http://dx.doi.org/10.1017/s0890060400002079.

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AbstractThis paper proposes and evaluates a neural network-based method for simulating manufacturing processes that exhibit both noncontinuous and stochastic behavior processes more conventionally modeled, using discrete-event simulation algorithms. The incentive for developing the technique is its potential for rapid execution of a simulation through parallel processing, and facilitation of the development and improvement of models particularly where there is limited theory describing the dependence between component processes. A brief introduction is provided to a radial-Gaussian neural network architecture and training process, the system adopted for the work presented in this paper. A description of the basic approach proposed for applying this technology to simulation is then described. This involves the use of a modularized neural network approach to model construction and the prediction of the occurrence of events using information retained from several previous states of the simulation. A class of earth-moving systems, comprising a push-dozer and a fleet of scrapers, is used as the basis for assessing the viability and performance of the proposed approach. A series of experiments show the neural network to be capable of both capturing the characteristic behavior and making an accurate prediction of production rates of scraper-based earth-moving systems. The paper concludes with an indication of some areas for further development and evaluation of the technique.

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Miao, Y. P. "Workflow Simulation Modeling Based on Discrete Event Approach." Advanced Materials Research 69-70 (May 2009): 700–704. http://dx.doi.org/10.4028/www.scientific.net/amr.69-70.700.

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In order to apply simulation to analysis, evaluation and optimization of the workflow performances, workflow process model for simulation is firstly formalized. Then workflow simulation model is bulit based on discrete event approach. Finally the supporting software tool system has been developed which shows feasibility of the proposed method.

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Yao, Ming Hai, Xiao Ji Chen, and Lei Zuo. "Customer Arrival Event Processing on Computer Simulation for Discrete Event System." Applied Mechanics and Materials 513-517 (February 2014): 2133–36. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.2133.

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Discrete event systems are widely used in the production and life, it is difficult to use conventional differential equations, differential equations, and other models to describe, the theoretical analysis method is difficult to obtain analytical solutions, computer simulation techniques to solve these problems provides an effective means. Arrival event is a typical discrete system event; on arrival event handling is always one of the difficulties of computer simulation, in this paper, banking customer arrival system as an example to study. For banks queuing system, customers arrive to obey the parameter of Poisson distribution is, the probability mass function through the distribution curves and cumulative distribution function curves to study the distribution of customer arrival; construction of single-queue multi-server system of customer arrival event subroutine flow chart, and processing steps will be described. Content of this study, it is suitable for the developed area bank to adopt "number ticket machine" approach to service.

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She, Ji, Woodam Chung, and David Kim. "Discrete-Event Simulation of Ground-Based Timber Harvesting Operations." Forests 9, no. 11 (October 31, 2018): 683. http://dx.doi.org/10.3390/f9110683.

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Operational studies are necessary to support production and management decisions of forest industries. A time study (TS) approach is widely used in timber harvesting operations to understand the performance of individual harvesting machines as well as the entire system. However, several limitations of the TS approach include the use of generalized utilization rates, incapability of capturing interactions among equipment, and model extrapolation in sensitivity analysis. In this study, we demonstrated the use of discrete event simulation (DES) techniques in modeling a ground-based timber harvesting system, and compared the DES results with those of the TS model developed with the same observed data. Although both TS and DES models provided similar estimation results for individual machine cycle times and productivities, the estimated machine utilization rates were somewhat different due to the difference in synthesizing machine processes in each approach. Our sensitivity analysis and model expansion to simulate a hypothetical harvesting system suggest that the DES approach may become an appropriate method for analyzing complex systems especially where interactions among different machine processes are unknown.

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Kamrud, Alexander J., Douglas D. Hodson, Gilbert L. Peterson, and Brian G. Woolley. "Unified behavior framework in discrete event simulation systems." Journal of Defense Modeling and Simulation: Applications, Methodology, Technology 14, no. 4 (January 10, 2017): 471–81. http://dx.doi.org/10.1177/1548512916683450.

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Intelligent agents provide simulations a means to add lifelike behavior in place of manned entities. When implemented, typically a single intelligent agent model (or approach to defining decision making), such as rule-based, behavior trees, neural networks, etc., is selected. This choice introduces restrictions into what behaviors agents can manifest, and can require significant testing in edge cases. This paper presents the incorporation and application of the Unified Behavior Framework (UBF) into the Advanced Framework for Simulation, Integration, and Modeling environment. The UBF provides the flexibility to implement any and all behavior-based systems, allowing the developer to rapidly assemble a decision making agent that leverages multiple paradigms or approaches. The UBF achieves this by leveraging several key software engineering principles: modular design, scalability through reduced code complexity, simplified development and testing through abstraction, and the promotion of code reuse. The use of UBF to define intelligent agents within a 2v2 Integrated Air Defense System is demonstrated.

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Aliyu, Hamzat Olanrewaju, Oumar Maïga, and Mamadou Kaba Traoré. "The high level language for system specification: A model-driven approach to systems engineering." International Journal of Modeling, Simulation, and Scientific Computing 07, no. 01 (March 2016): 1641003. http://dx.doi.org/10.1142/s1793962316410038.

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We present HiLLS (High Level Language for System Specification), a graphical formalism that allows to specify Discrete Event System (DES) models for analysis using methodologies like simulation, formal methods and enactment. HiLLS’ syntax is built from the integration of concepts from System Theory and Software Engineering aided by simple concrete notations to describe the structural and behavioral aspects of DESs. This paper provides the syntax of HiLLS and its simulation semantics which is based on the Discrete Event System Specification (DEVS) formalism. From DEVS-based Modeling and Simulation (M&S) perspective, HiLLS is a platform-independent visual language with generic expressions that can serve as a front-end for most existing DEVS-based simulation environments with the aid of Model-Driven Engineering (MDE) techniques. It also suggests ways to fill some gaps in existing DEVS-based visual formalisms that inhibit complete specification of the behavior of complex DESs. We provide a case study to illustrate the core features of the language.

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Chaos, Dictino, Joaquín Aranda, Rocío Munoz, José Manuel Díaz, and Jesús M. de la Cruz. "DISCRETE EVENT BASED APPROACH TO THE SIMULATION OF A CONTINUOUS NAVAL SYSTEM." IFAC Proceedings Volumes 40, no. 17 (2007): 223–28. http://dx.doi.org/10.3182/20070919-3-hr-3904.00040.

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Pohlmann, Werner. "A fixed point approach to parallel discrete event simulation." Acta Informatica 28, no. 7 (July 1991): 611–29. http://dx.doi.org/10.1007/bf01178679.

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Ricker, S. L., N. Sarkar, and K. Rudiet. "A discrete-event systems approach to modeling dextrous manipulation." Robotica 14, no. 5 (September 1996): 515–25. http://dx.doi.org/10.1017/s0263574700020002.

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SUMMARYTo perform dextrous manipulation efficiently, it is necessary to coordinate the interactions of many component processes. This paper investigates one approach to coordination: discrete-event systems. The applicability of discrete-event systems to the modeling of dextrous manipulation tasks is studied. Discrete-event control theory offers formal methods for determining whether a coordinator of the components can be generated. A representative dextrous manipulation task, the planar Grasp-Lift-Replace task of Howe and Cutkosky, is presented as a discrete-event process. The task is extended to include two-fingered exploratory procedures. The effectiveness of the discrete-event system approach is illustrated through simulations of several test cases.

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Dayarathna, Vidanelage L., Hebah Mismesh, Mohammad Nagahisarchoghaei, and Aziz Alhumoud. "A DISCRETE EVENT SIMULATION (DES) BASED APPROACH TO MAXIMIZE THE PATIENT THROUGHPUT IN OUTPATIENT CLINIC." Engineering Science & Technology Journal 1, no. 1 (June 23, 2020): 1–11. http://dx.doi.org/10.51594/estj.v1i1.36.

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The healthcare system is a complex system which exhibits conditions of uncertainty, ambiguity emergence that incurs incoming patient congestion. Discrete event simulation (FlexSim) is considered as a viable decision support tool in analyzing a system for improvement. Using a data-driven discrete event simulation approach, this paper portrays a comprehensive analysis to maximize the number of patients in an on-campus clinic, located at Mississippi State University. The outcome of the analysis of current system exhibits that deploying a few nurse practitioners results in bottlenecks which decreases the systems’ throughput substantially due to the overall longer patients’ waiting time. Access to the laboratory is characterized through multi-server queuing network, arrival process is followed discrete distributions, and batch sizes and arrival times are stochastic in nature. In an effort to plummet inpatient congestion at the outpatient clinic, by using empirically calibrated simulation model, we will figure out the best balance between the number of the lab technician and incoming patient during working hour. An analysis of optimal solutions is demonstrated, which is followed by recommendation and avenues for future research.

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Azzabi, Olfa, Chakib Ben Njima, and Hassani Messaoud. "New Approach of Diagnosis by Timed Automata." International Journal of Ambient Computing and Intelligence 8, no. 3 (July 2017): 76–93. http://dx.doi.org/10.4018/ijaci.2017070105.

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The Discrete Event Systems (DES) is a nonlinear dynamic system with discrete state and event evolution. In this article, we are interested in the diagnosis of failures with Timed Automata. The proposed approach is based on the operating time and it is applicable to any system whose dynamic evolution depends not only on the order of discrete events but also on their periods as in industrial processes. The most important part of this work is the construction of a diagnoser which uses observables events to detect and locate the faults. We present on the last part of this work results of the study of the performance of the diagnosis showing the power of this diagnostic approach. An implementation on a hydraulic system is made to illustrate the proposed steps. It put in evidence the effectiveness of this approach. The model of the simulation phase is done using Matlab / Simulink / stateflow.

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Ghani, Usman, Radmehr Monfared, and Robert Harrison. "Integration approach to virtual-driven discrete event simulation for manufacturing systems." International Journal of Computer Integrated Manufacturing 28, no. 8 (June 11, 2014): 844–60. http://dx.doi.org/10.1080/0951192x.2014.924159.

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Kang, Bong Gu, Kyung-Min Seo, and Tag Gon Kim. "Machine learning-based discrete event dynamic surrogate model of communication systems for simulating the command, control, and communication system of systems." SIMULATION 95, no. 8 (November 28, 2018): 673–91. http://dx.doi.org/10.1177/0037549718809890.

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Command and control (C2) and communication are at the heart of successful military operations in network-centric warfare. Interoperable simulation of a C2 system model and a communication (C) system model may be employed to interactively analyze their detailed behaviors. However, such simulation would be inefficient in simulation time for analysis of combat effectiveness of the C2 model against possible input combinations while considering the communication effect in combat operations. This study proposes a discrete event dynamic surrogate model (DEDSM) for the C model, which would be integrated with the C2 model and simulated. The proposed integrated simulation reduces execution time markedly in analysis of combat effectiveness without sacrificing the accuracy reflecting the communication effect. We hypothesize the DEDSM as a probabilistic priority queuing model whose semantics is expressed in a discrete event systems specification model with some characteristic functions unknown. The unknown functions are identified by machine learning with a data set generated by interoperable simulation of the C2 and C models. The case study with the command, control, and communication system of systems first validates the proposed approach through an equivalence test between the interoperable simulation and the proposed one. It then compares the simulation execution times and the number of events exchanged between the two simulations.

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FITZGERALD, J. S., P. G. LARSEN, K. G. PIERCE, and M. H. G. VERHOEF. "A formal approach to collaborative modelling and co-simulation for embedded systems." Mathematical Structures in Computer Science 23, no. 4 (July 8, 2013): 726–50. http://dx.doi.org/10.1017/s0960129512000242.

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The effective use of model-based formal methods in the development of complex embedded systems requires the integration of discrete-event models of controllers with continuous-time models of their environments. This paper proposes a new approach to the development of such combined models (co-models), in which an initial discrete-event model may include approximations of continuous-time behaviour that can subsequently be replaced by couplings to continuous-time models. An operational semantics of co-simulation allows the discrete and continuous models to run on their respective simulators and managed by a coordinating co-simulation engine. This permits the exploration of the composite co-model's behaviour in a range of operational scenarios. The approach has been realised using the Vienna Development Method (VDM) as the discrete-event formalism, and 20-sim as the continuous-time framework, and has been applied successfully to a case study based on the distributed controller for a personal transporter device.

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Liu, Fei, and Hongmei Zhang. "A class of extended time Petri nets for modeling and simulation of discrete event systems." SIMULATION 94, no. 8 (December 7, 2017): 753–62. http://dx.doi.org/10.1177/0037549717742716.

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Time Petri nets (TPNs) have been widely used for modeling discrete event systems such as manufacturing, supply chain, and military systems. However, TPNs still have many drawbacks in some scenarios where an operation or process is associated with probability, and also lack appropriate simulation algorithms for analyzing different types of systems. In this paper, we address these two issues by proposing a class of extended time Petri nets (ETPNs) and presenting an appropriate simulation algorithm. We illustrate and validate our approach using a hypothetic command and control system, which shows that this approach could be a powerful tool for modeling and analyzing discrete event systems.

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Bursi, Fabio, Andrea Ferrara, Andrea Grassi, and Chiara Ronzoni. "Simulating Continuous Time Production Flows in Food Industry by Means of Discrete Event Simulation." International Journal of Food Engineering 11, no. 1 (February 1, 2015): 139–50. http://dx.doi.org/10.1515/ijfe-2014-0002.

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Abstract The paper presents a new framework for carrying out simulations of continuous-time stochastic processes by exploiting a discrete event approach. The application scope of this work mainly refers to industrial production processes executed on a continuous flow of material (e.g. food and beverage industry) as well as production processes working on discrete units but characterized by a high speed flow (e.g. automated packaging lines). The proposed model, developed adopting the Discrete EVent system Specification (DEVS) formalism, defines a single generalized base unit able to represent, by means of an event scheme generated by state changes, the base behaviors needed for the modeling of a generic manufacturing unit, that is, (i) breakdowns and repairs, (ii) speed and accumulation, and (iii) throughput time. Moreover, the possibility to keep trace of additional measures of parameters related to the process and the flowing material (i.e. temperature, concentration of pollutant, and so on) is also considered. Since these parameters can change over time in a continuous manner, a specific discretization approach has been introduced to avoid the need to integrate parameter variation functions over time.

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Doja, Albert, Laurent Capocchi, and Jean-François Santucci. "Computational challenges to test and revitalize Claude Lévi-Strauss transformational methodology." Big Data & Society 8, no. 2 (July 2021): 205395172110378. http://dx.doi.org/10.1177/20539517211037862.

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The ambition and proposal for data modeling of myths presented in this paper is to link contemporary technical affordances to some canonical projects developed in structural anthropology. To articulate the theoretical promise and innovation of this proposal, we present a discrete-event system specification modeling and simulation approach in order to perform a generative analysis and a dynamic visualization of selected narratives, aimed at validating and revitalizing the transformational and morphodynamic theory and methodology proposed by Claude Lévi-Strauss in his structural analysis of myth. After an analysis of Lévi-Strauss’s transformational methodology, we describe in detail how discrete-event system specification models are implemented and developed in the framework of a DEVSimPy software environment. The validation of the method involves a discrete-event system specification simulation based on the extension of discrete-event system specification models dedicated to provide a dynamic Google Earth visualization of the selected myth. Future work around the discrete-event system specification formalism in anthropology is described as well as future applications regarding the impact of computational models (discrete-event system specification formalism, Bayesian inferences, and object-oriented features) to new contemporary anthropological domains.

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Lee, Hyo-Jik, Sung-Hyun Kim, and Byung-Suk Park. "DISCRETE EVENT SYSTEM SIMULATION APPROACH FOR AN OPERATION ANALYSIS OF A HEADEND PROCESS FACILITY." Nuclear Engineering and Technology 41, no. 5 (June 30, 2009): 739–46. http://dx.doi.org/10.5516/net.2009.41.5.739.

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Liao, Jingjing. "A Key Event Path Analysis Approach for Integrated Systems." Modelling and Simulation in Engineering 2012 (2012): 1–7. http://dx.doi.org/10.1155/2012/383129.

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By studying the key event paths of probabilistic event structure graphs (PESGs), a key event path analysis approach for integrated system models is proposed. According to translation rules concluded from integrated system architecture descriptions, the corresponding PESGs are constructed from the colored Petri Net (CPN) models. Then the definitions of cycle event paths, sequence event paths, and key event paths are given. Whereafter based on the statistic results after the simulation of CPN models, key event paths are found out by the sensitive analysis approach. This approach focuses on the logic structures of CPN models, which is reliable and could be the basis of structured analysis for discrete event systems. An example of radar model is given to characterize the application of this approach, and the results are worthy of trust.

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Biazen, Melkamu Ambelu, and Sisay Geremew Gebeyehu. "Comparative Analysis of Analytical and Discrete-Event Simulation Models of Assembly Line Systems." Journal of Engineering, Project, and Production Management 9, no. 2 (July 1, 2019): 132–41. http://dx.doi.org/10.2478/jeppm-2019-0015.

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Abstract System-wide performance analysis of manufacturing setup helps a company to stay competitive. This can be done by selecting appropriate performance analysis tool which can save time and effort. As a problem assembly line systems are difficult to completely model and analyze using either of analytical or discrete-event simulation (DES) models. The main objective of this study is to analyze the distinct modeling capabilities of analytical modeling approach and DES approach so as to take their respective primacy for analysis of particular pertinent parameters suitable for Tana Communication (TC assembly line). Both analytical and discrete-event simulation models are developed for TC production process using decomposition approach and AnyLogic software. The results from the two models for work in process, queue cycle time, cycle time and resource utilization have high degree of agreement. By making reassignment of operators from the idle stage to the bottleneck stage the system waiting time and work in process is reduced by 12% and 13% respectively from the proposed model.

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Cortes, Edwin, Luis Rabelo, Alfonso T. Sarmiento, and Edgar Gutierrez. "Design of Distributed Discrete-Event Simulation Systems Using Deep Belief Networks." Information 11, no. 10 (October 1, 2020): 467. http://dx.doi.org/10.3390/info11100467.

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In this research study, we investigate the ability of deep learning neural networks to provide a mapping between features of a parallel distributed discrete-event simulation (PDDES) system (software and hardware) to a time synchronization scheme to optimize speedup performance. We use deep belief networks (DBNs). DBNs, which due to their multiple layers with feature detectors at the lower layers and a supervised scheme at the higher layers, can provide nonlinear mappings. The mapping mechanism works by considering simulation constructs, hardware, and software intricacies such as simulation objects, concurrency, iterations, routines, and messaging rates with a particular importance level based on a cognitive approach. The result of the mapping is a synchronization scheme such as breathing time buckets, breathing time warp, and time warp to optimize speedup. The simulation-optimization technique outlined in this research study is unique. This new methodology could be realized within the current parallel and distributed simulation modeling systems to enhance performance.

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Xu, Jianfei, S. M. AbouRizk, and Cam Fraser. "Integrated three-dimensional computer-aided design and discrete-event simulation models." Canadian Journal of Civil Engineering 30, no. 2 (April 1, 2003): 449–59. http://dx.doi.org/10.1139/l02-110.

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Three-dimensional computer-aided design (3D-CAD) systems that integrate critical path method (CPM) algorithms, commonly referred to as four-dimensional computer-aided design (4D-CAD), have received a high level of interest over the past few years due to the insight they offer into constructability and feasibility analysis. This paper outlines an approach that facilitates this modeling method through integration between a commercial 3D-CAD software package and a discrete-event simulation tool. This approach employs a product-based modeling method that integrates simulation models with CAD drawings to provide real-time analysis and improved model accuracy in modeling construction operations. By integrating with 3D-CAD drawings, the models require much less data entry and provide a much higher degree of accuracy. Additionally, during the course of a project, resource and time consumption data can be collected and used to continually update the model, minimizing the use of assumptions and generalized data. This paper provides a short background and literature review to contextualize the problem statement, describes the product atomic component (PAC) used to integrate 3D-CAD and the simulation model, outlines some of the implementation issues in a simulation context, and presents a prototype system with an example application for an earthmoving project.Key words: 4D-CAD, CPM, product atomic component, simulation modeling, integration, earthmoving.

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Naghdy, Fazel, and Naeem Anjum. "Discrete-event modelling, simulation and control of a distributed manipulation environment." Robotica 15, no. 2 (March 1997): 181–98. http://dx.doi.org/10.1017/s0263574797000209.

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Conventional robotics has proved to be inflexible and non-generic. The concept of Distributed Manipulation Environment (DME) is introduced to overcome some of these shortcomings. This concept proposes a distributed approach to robotics and flexible automation. The work is concerned with modelling, simulation and event based control of DME. The modelling, conducted both at the atomic and the coupled level, is quite generic and provides a framework for static and dynamic behaviour analysis of DME systems. The simulation models serve as a mean of performance evaluation of the system on a computer before the actual implementation in real time. The event-based controller provides a simple and robust control scheme. The controller, itself, can be tested, validated and finely tuned through simulation before implementation. The feasibility of the modelling technique is demonstrated through a case study.

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Alrabghi, Abdullah, and Ashutosh Tiwari. "A novel approach for modelling complex maintenance systems using discrete event simulation." Reliability Engineering & System Safety 154 (October 2016): 160–70. http://dx.doi.org/10.1016/j.ress.2016.06.003.

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Odedairo, B. O., and N. Nwabuokei. "Framework for Operational Performance Measurements in Small and Medium Scale Industries Using Discrete Event Simulation Approach." Engineering, Technology & Applied Science Research 8, no. 4 (August 18, 2018): 3103–7. http://dx.doi.org/10.48084/etasr.2106.

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Globally, production systems must cope with limitations arising from variabilities and complexities due to globalization and technological advancements. To survive in spite of these challenges, critical process measures need to be closely monitored to ensure improved system performance. For production managers, the availability of accurate measurements which depict the status of production activities in real time is desired. This study is designed to develop an operational data decision support tool (ODATA-DST) using discrete event simulation approach. The work-in-process and processing time of each workstation/buffer station in a bottled water production system were investigated. The status of each job as they move through the system was used to simulate a routing matrix. The production output data for 50cl and 75cl product from 2014-2016 were collected. A mathematical model for routing jobs from the point of arrival to the point of departure was developed using discrete event simulation. A graphical user interface (GUI) was designed based on the factory’s performance measurement algorithm. Simulating the factory’s work-in-process with respect to internal benchmarks yielded a cycle time of 4.4, 6.23, 5.04 and throughput of 0.645, 0.455, 0.637 for best case scenario, worst case scenario and practical worst case scenario respectively. The factory performed below the simulated benchmark at 26%, 28%, 28% for the 50cl and at 51%, 54%, 59% for 75cl regarding the year 2014, 2015 and 2017 respectively. Performance measurement decision support tool has been developed to enhance the production manager’s decision making capability. The tool can improve production data analysis and performance predictions.

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Alvarado, Michelle M., Tanisha G. Cotton, Lewis Ntaimo, Eduardo Pérez, and William R. Carpentier. "Modeling and simulation of oncology clinic operations in discrete event system specification." SIMULATION 94, no. 2 (May 31, 2017): 105–21. http://dx.doi.org/10.1177/0037549717708246.

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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.

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Sánchez, Álvaro García, Miguel Ortega-Mier, and Roberto Arranz. "Discrete-Event Simulation Models for Assessing Incidents in Railway Systems." International Journal of Information Systems and Supply Chain Management 4, no. 2 (April 2011): 1–14. http://dx.doi.org/10.4018/jisscm.2011040101.

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This paper presents a discrete event simulation model developed with a commercial environment. A modular approach is adopted, which facilitates building models for different railway systems. A key feature of this simulator is that it simultaneously models train movements and passenger behavior. The simulator has been used to assess two different policies when short incidents occur. Incidents are characterized by different factors, which are analyzed for both policies. A case-study is presented based on a subsystem of the commuter train network of the province of Madrid in Spain.

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Tang, Wenjie, Wentong Cai, Yiping Yao, Xiao Song, and Feng Zhu. "An alternative approach for collaborative simulation execution on a CPU+GPU hybrid system." SIMULATION 96, no. 3 (November 14, 2019): 347–61. http://dx.doi.org/10.1177/0037549719885178.

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In the past few years, the graphics processing unit (GPU) has been widely used to accelerate time-consuming models in simulations. Since both model computation and simulation management are main factors that affect the performance of large-scale simulations, only accelerating model computation will limit the potential speedup. Moreover, models that can be well accelerated by a GPU could be insufficient, especially for simulations with many lightweight models. Traditionally, the parallel discrete event simulation (PDES) method is used to solve this class of simulation, but most PDES simulators only utilize the central processing unit (CPU) even though the GPU is commonly available now. Hence, we propose an alternative approach for collaborative simulation execution on a CPU+GPU hybrid system. The GPU supports both simulation management and model computation as CPUs. A concurrency-oriented scheduling algorithm was proposed to enable cooperation between the CPU and the GPU, so that multiple computation and communication resources can be efficiently utilized. In addition, GPU functions have also been carefully designed to adapt the algorithm. The combination of those efforts allows the proposed approach to achieve significant speedup compared to the traditional PDES on a CPU.

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Nutaro, James, Phani Teja Kuruganti, Vladimir Protopopescu, and Mallikarjun Shankar. "The split system approach to managing time in simulations of hybrid systems having continuous and discrete event components." SIMULATION 88, no. 3 (May 10, 2011): 281–98. http://dx.doi.org/10.1177/0037549711401000.

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The efficient and accurate management of time in simulations of hybrid models is an outstanding engineering problem. General a priori knowledge about the dynamic behavior of the hybrid system (i.e. essentially continuous, essentially discrete, or ‘truly hybrid’) facilitates this task. Indeed, for essentially discrete and essentially continuous systems, existing software packages can be conveniently used to perform quite sophisticated and satisfactory simulations. The situation is different for ‘truly hybrid’ systems, for which direct application of existing software packages results in a lengthy design process, cumbersome software assemblies, inaccurate results, or some combination of these independent of the designer’s a priori knowledge about the system’s structure and behavior. The main goal of this paper is to provide a methodology whereby simulation designers can use a priori knowledge about the hybrid model’s structure to build a straightforward, efficient, and accurate simulator with existing software packages. The proposed methodology is based on a formal decomposition and re-articulation of the hybrid system; this is the main theoretical result of the paper. To set the result in the right perspective, we briefly review the essentially continuous and essentially discrete approaches, which are illustrated with typical examples. Then we present our new, split system approach, first in a general formal context, then in three more specific guises that reflect the viewpoints of three main communities of hybrid system researchers and practitioners. For each of these variants we indicate an implementation path. Our approach is illustrated with an archetypal problem of power grid control.

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APAK, Sinan, and Sami ERCAN. "Simulation Based Optimization for World Line Card Production System." An International Journal of Optimization and Control: Theories & Applications (IJOCTA) 2, no. 2 (May 28, 2012): 95–104. http://dx.doi.org/10.11121/ijocta.01.2012.00107.

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Simulation based decision support system is one of the commonly used tool to examine complex production systems. The simulation approach provides process modules which can be adjusted with certain parameters by using data relatively easily obtainable in production process. World Line Card production system simulation is developed to evaluate the optimality of existing production line via using discrete event simulation model with variaty of alternative proposals. The current production system is analysed by a simulation model emphasizing the bottlenecks and the poorly utilized production line. Our analysis identified some improvements and efficient solutions for the existing system.

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Florea, Ion, and Corina-Ştefania Nǎnǎu. "A simulation algorithm for a single server retrial queuing system with batch arrivals." Analele Universitatii "Ovidius" Constanta - Seria Matematica 23, no. 1 (January 1, 2015): 83–98. http://dx.doi.org/10.1515/auom-2015-0007.

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AbstractMany systems of real word are modeled by retrial queuing system with batch arrivals. Analytical formulas for this class of systems are complicated and address only particular cases. The paper presents a study approach for this kind of systems, based on discrete event simulation. It is shown that the given algorithm has a polynomial complexity. Also, the object-oriented design we used for implementation is sketched.

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Gruer, P., A. Koukam, and B. Mazigh. "Modeling and quantitative analysis of discrete event systems: A statecharts based approach." Simulation Practice and Theory 6, no. 4 (May 1998): 397–411. http://dx.doi.org/10.1016/s0928-4869(97)00029-3.

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Sava, Alexandru Tiberiu, and Hassane Alla. "A control synthesis approach for time discrete event systems." Mathematics and Computers in Simulation 70, no. 5-6 (February 2006): 250–65. http://dx.doi.org/10.1016/j.matcom.2005.11.001.

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Koukam, A., B. Mazigh, P. Gruer, and V. Hilaire. "A Multiview Approach to Modeling and Analysis of Discrete Event Systems." Systems Analysis Modelling Simulation 43, no. 6 (June 2003): 721–40. http://dx.doi.org/10.1080/0232929021000015185.

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Munira Ibrahim, Ireen, Choong-Yeun Liong, Sakhinah Abu Bakar, and Ahmad Farid Najmudd. "Performance Improvement of the Yellow Zone in Emergency Department using Discrete Event Simulation Approach." International Journal of Engineering & Technology 7, no. 4.33 (December 9, 2018): 102. http://dx.doi.org/10.14419/ijet.v7i4.33.23509.

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Overcrowding is a major concern for the Emergency Department (ED) management at the public hospital under study. Although the number of patients in the Yellow Zone (YZ) of the department represents only 30% of the total visiting patient per day, the Key Performance Indicator (KPI) of the zone’s patients’ LOS (LOS) as well as waiting time are not achievable due to the resources constraints. Therefore, this paper discusses the application of Discrete Event Simulation (DES) approach on modeling the YZ’s daily operations. The model was developed using Arena software to assist the ED management to better understand their system behavior and causes for the high patients’ LOS and waiting time. The simulation outputs show that the bottleneck of the system is waiting for an available resource. A few scenarios were designed based on the discussion made with the ED management for possible improvement. The results show a significant reduction of 25% and 35% in the total average of patients’ LOS for the patients of the observation unit and the intensive unit respectively. Meanwhile, for the total average patients’ waiting time, the results show a reduction of 34% for the observation unit and 29% reduction for the intensive unit.

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Latorre-Biel, Juan-Ignacio, Emilio Jiménez-Macías, and Mercedes Pérez de la Parte. "Equivalent and Efficient Optimization Models for an Industrial Discrete Event System with Alternative Structural Configurations." Complexity 2018 (2018): 1–14. http://dx.doi.org/10.1155/2018/5341346.

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Discrete event systems in applications, such as industry and supply chain, may show a very complex behavior. For this reason, their design and operation may be carried out by the application of optimization techniques for decision making in order to obtain their highest performance. In a general approach, it is possible to implement these optimization techniques by means of the simulation of a Petri net model, which may require an intensive use of computational resources. One key factor in the computational cost of simulation-based optimization is the size of the model of the system; hence, it may be useful to apply techniques to reduce it. This paper analyzes the relationship between two Petri net formalisms, currently used in the design of discrete event systems, where it is usual to count on a set of alternative structural configurations. These formalisms are a particular type of parametric Petri nets, called compound Petri nets, and a set of alternative Petri nets. The development of equivalent models under these formalisms and the formal proof of this equivalence are the main topics of the paper. The basis for this formal approach is the graph of reachable markings, a powerful tool able to represent the behavior of a discrete event system and, hence, to show the equivalence between two different Petri net models. One immediate application of this equivalence is the substitution of a large model of a system by a more compact one, whose simulation may be less demanding in the use of computational resources.

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Subramanian, K., and M. Zargham. "Distributed and Parallel Demand Driven Logic Simulation Algorithms." VLSI Design 1, no. 2 (January 1, 1994): 169–79. http://dx.doi.org/10.1155/1994/12503.

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Based on the demand-driven approach, distributed and parallel simulation algorithms are proposed. Demand-driven simulation ties to minimize the number of component evaluations by restricting to only those component computations required for the watched output requests. For a specific output value request, the input line values that are required are requested to the respective component. The process continues until known signal values are needed (system input signal values). We present a distributed demand-driven algorithm with infinite memory requirement (but still the memory required at each process is no greater than the sequential demand-driven simulation), and a parallel demand-driven simulation with finite memory requirement. In our algorithms, each component is assigned a logical process.The algorithms have been implemented on the Sequent Balance 8000 Multi-processor machine. Several sample circuits were simulated. The algorithms were compared with the distributed discrete-event simulation. Our distributed algorithm performed many times faster than the discrete-event simulation for cases when few results were needed. Parallel algorithm performed 2 to 4 times faster than the distributed discrete-event simulation.

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Anufriev, A. "Study of Hybrid Dynamical Approach for Manufacturing Systems Scheduling by Discrete Event Simulation." IFAC Proceedings Volumes 36, no. 3 (April 2003): 95–100. http://dx.doi.org/10.1016/s1474-6670(17)37741-8.

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Paolucci, Massimo, and Raffaele Pesenti. "An Object-Oriented Approach to Discrete-Event Simulation Applied to Underground Railway Systems." SIMULATION 72, no. 6 (June 1999): 372–83. http://dx.doi.org/10.1177/003754979907200601.

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Rajendran, Suchithra, and Jake Shulman. "Study of emerging air taxi network operation using discrete-event systems simulation approach." Journal of Air Transport Management 87 (August 2020): 101857. http://dx.doi.org/10.1016/j.jairtraman.2020.101857.

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Ju, Jiahe, Bochen Shi, Zhujun Yu, Yicheng Zhu, and Zhengming Zhao. "Backward Discrete State Event-Driven Approach for Simulation of Stiff Power Electronic Systems." IEEE Access 9 (2021): 28573–81. http://dx.doi.org/10.1109/access.2021.3058417.

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Makarov, Valery, Albert Bakhtizin, Gayane Beklaryan, and Andranik Akopov. "Digital plant: methods of discrete-event modeling and optimization of production characteristics." Business Informatics 15, no. 2 (June 30, 2021): 7–20. http://dx.doi.org/10.17323/2587-814x.2021.2.7.20.

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This article presents a new approach to the development of a ‘digital twin’ of a manufacturing enterprise, using a television manufacturing plant as the case study. The feature of the proposed approach is the use of hybrid methods of agent-based modeling and discrete-event simulation in order to implement a simulation model of a complex production process for assembling final products from supplied components. The most important requirement for such a system is the integration of all key chains of a digital plant: conveyor lines, warehouses with components and final products (TVs), sorting and conveyor system, assembly unit, technical control department, packing unit, etc. The proposed simulation model is implemented in the AnyLogic system, which supports the possibility of using agent-based and discrete-event modeling methods within one model. The system also supports using the built-in genetic algorithm to optimize the main parameters of the model: the most important production characteristics (for example, assembly time of a product, the number of employees involved in assembly, quality control and packaging processes). Optimization experiments were completed with the help of the developed model at various intensities of loading conveyor lines with components, various restrictions on labor resources, etc. Three scenarios of the production system behavior are investigated: the absence of the components deficit with the possibility of significantly increasing the labor resource involved, a components deficit while demand for final products is maintained, and the presence of hard restrictions on the number of employees who can be involved in the processes under conditions of components deficit.

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Prajapat, N., C. Turner, A. Tiwari, D. Tiwari, and W. Hutabarat. "Real-time discrete event simulation: a framework for an intelligent expert system approach utilising decision trees." International Journal of Advanced Manufacturing Technology 110, no. 11-12 (September 17, 2020): 2893–911. http://dx.doi.org/10.1007/s00170-020-06048-5.

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Albrecht, Florian, Oliver Kleine, and Eberhard Abele. "Planning and Optimization of Changeable Production Systems by Applying an Integrated System Dynamic and Discrete Event Simulation Approach." Procedia CIRP 17 (2014): 386–91. http://dx.doi.org/10.1016/j.procir.2014.01.039.

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Lindberg, Therese, Fredrik Johansson, Anders Peterson, and Andreas Tapani. "Discrete Event Simulation of Bus Terminals: A Modular Approach with a High Spatial Resolution." Journal of Advanced Transportation 2021 (January 27, 2021): 1–17. http://dx.doi.org/10.1155/2021/8862893.

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Interchange stations with their many connecting modes and lines are central for a high-quality public transport system. Bus access at the station needs to operate reliably and efficiently in order to prevent congestion and queues. To this end, a conceptual simulation model for evaluation of bus terminal operations is presented in this paper. It is based on discrete event simulation and able to describe the detailed movements and interactions that occur between vehicles at larger terminals. The model has a modular approach, where common spatial sections at terminals are represented by modules that can be easily combined into many different terminal layouts. An implementation of the model is presented and, as a first sensitivity test, applied in a numerical experiment representing Norrköping interchange station in Sweden. The results indicate that the model can be a useful tool in planning processes.

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Yip, Kenneth, Suk-King Pang, Kui-Tim Chan, Chi-Kuen Chan, and Tsz-Leung Lee. "Improving outpatient phlebotomy service efficiency and patient experience using discrete-event simulation." International Journal of Health Care Quality Assurance 29, no. 7 (August 8, 2016): 733–43. http://dx.doi.org/10.1108/ijhcqa-08-2015-0093.

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Purpose – The purpose of this paper is to present a simulation modeling application to reconfigure the outpatient phlebotomy service of an acute regional and teaching hospital in Hong Kong, with an aim to improve service efficiency, shorten patient queuing time and enhance workforce utilization. Design/methodology/approach – The system was modeled as an inhomogeneous Poisson process and a discrete-event simulation model was developed to simulate the current setting, and to evaluate how various performance metrics would change if switched from a decentralized to a centralized model. Variations were then made to the model to test different workforce arrangements for the centralized service, so that managers could decide on the service’s final configuration via an evidence-based and data-driven approach. Findings – This paper provides empirical insights about the relationship between staffing arrangement and system performance via a detailed scenario analysis. One particular staffing scenario was chosen by manages as it was considered to strike the best balance between performance and workforce scheduled. The resulting centralized phlebotomy service was successfully commissioned. Practical implications – This paper demonstrates how analytics could be used for operational planning at the hospital level. The authors show that a transparent and evidence-based scenario analysis, made available through analytics and simulation, greatly facilitates management and clinical stakeholders to arrive at the ideal service configuration. Originality/value – The authors provide a robust method in evaluating the relationship between workforce investment, queuing reduction and workforce utilization, which is crucial for managers when deciding the delivery model for any outpatient-related service.

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Cannella, Salvatore, Manfredi Bruccoleri, Ana Paula Barbosa Póvoa, and Susana Relvas. "Methodological approach to study the dynamics of production networks: discrete-event simulation modelling." International Journal of Logistics Systems and Management 16, no. 2 (2013): 211. http://dx.doi.org/10.1504/ijlsm.2013.056174.

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Zhecheng, Zhu. "An online short-term bed occupancy rate prediction procedure based on discrete event simulation." Journal of Hospital Administration 3, no. 4 (February 18, 2014): 37. http://dx.doi.org/10.5430/jha.v3n4p37.

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In recent years, population growth and aging society impose large pressure on the resource requirement in Singapore public hospital system. Beds are one of the most critical resources in healthcare system. How to manage beds efficiently is an important and challenging task for the health service providers in any healthcare systems. One frequently used performance indicator of bed management is bed occupancy rate, which measures the bed utilization. In this paper, an online prediction procedure based on discrete event simulation is proposed and developed to predict bed occupancy rate in a short term period. Simulation results show that the predicted values are closer to the actual values with narrower confidence interval compared to the offline approach. Hence such a prediction procedure is able to provide a more reliable reference for decision making of the health service providers.

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Jackson, Ilya, Jurijs Tolujevs, and Tobias Reggelin. "The Combination of Discrete-Event Simulation and Genetic Algorithm for Solving the Stochastic Multi-Product Inventory Optimization Problem." Transport and Telecommunication Journal 19, no. 3 (September 1, 2018): 233–43. http://dx.doi.org/10.2478/ttj-2018-0020.

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Abstract The paper describes an eventual combination of discrete-event simulation and genetic algorithm to define the optimal inventory policy in stochastic multi-product inventory systems. The discrete-event model under consideration corresponds to the just-in-time inventory control system with a flexible reorder point. The system operates under stochastic demand and replenishment lead time. The utilized genetic algorithm is distinguished for a non-binary chromosome encoding, uniform crossover and two mutation operators. The paper contains a detailed description of the optimization technique and the numerical example of six- product inventory model. The proposed approach contributes to the field of industrial engineering by providing a simple, but still efficient way to compute nearly-optimal inventory parameters with regard to risk and reliability policy. Besides, the method may be applied in automated ordering systems.

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Shi, Peng, Fei Liu, and Ming Yang. "A Modified Statistical Process Control Approach for Warm-up Selection in Discrete-Event Simulation." Advanced Materials Research 187 (February 2011): 428–33. http://dx.doi.org/10.4028/www.scientific.net/amr.187.428.

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HLA-based simulation systems are multivariate discrete-event simulation systems, and sometimes with small samples in essential, for which exists initial transient issue. Simulation models begin in fixed initial values, which are always different from the steady state values. A variety of selection methods have been developed these years, but no one method could be recommended above others. Among these methods, the familiar statistical process control method is a popular way to deal with the warm-up selection, with the deficiency for multivariate and small samples. Based on SPC, individuals and moving range, multivariate exponentially weighted moving average chart for Individuals and Hotelling T2 method, a modified SPC method is proposed. The case of military domain simulation scenario and some empirical experiments, illustrate the validity of the modified SPC method.

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Journal articles on the topic 'Discrete-Event System Simulation Approach'

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