Modelling and controlling traffic behaviour with continuous Petri nets

Traffic systems are discrete systems that can be heavily populated. One way of overcoming the state explosion problem inherent to heavily populated discrete systems is to relax the discrete model. Continuous Petri nets (PN) represent a relaxation of the original discrete Petri nets that leads to a compositional formalism to model traffic behaviour. This paper introduces some new features of continuous Petri nets that are useful to obtain realistic but compact models for traffic systems. Combining these continuous PN models with discrete PN models of traffic lights leads to a hybrid Petri net model that is appropriate for predicting traffic behaviour, and for designing trac light controllers that minimize the total delay of the vehicles in the system

Enhancing the Supply Chain Performance by Integrating Simulated and Physical Agents into Organizational Information Systems

As the business environment gets more complicated, organizations must be able to respond to the business changes and adjust themselves quickly to gain their competitive advantages. This study proposes an integrated agent system, called SPA, which coordinates simulated and physical agents to provide an efficient way for organizations to meet the challenges in managing supply chains. In the integrated framework, physical agents coordinate with inter-organizations\' physical agents to form workable business processes and detect the variations occurring in the outside world, whereas simulated agents model and analyze the what-if scenarios to support physical agents in making decisions. This study uses a supply chain that produces digital still cameras as an example to demonstrate how the SPA works. In this example, individual information systems of the involved companies equip with the SPA and the entire supply chain is modeled as a hierarchical object oriented Petri nets. The SPA here applies the modified AGNES data clustering technique and the moving average approach to help each firm generalize customers\' past demand patterns and forecast their future demands. The amplitude of forecasting errors caused by bullwhip effects is used as a metric to evaluate the degree that the SPA affects the supply chain performance. The experimental results show that the SPA benefits the entire supply chain by reducing the bullwhip effects and forecasting errors in a dynamic environment.Supply Chain Performance Enhancement; Bullwhip Effects; Simulated Agents; Physical Agents; Dynamic Customer Demand Pattern Discovery

Simulation Modelling Practice and Theory

The influx of data in the world today needs analysis that no one method can handle. Some reports estimated the influx of data would reach 163 zitabytes by 2025, hence the need for simulation and modeling theory and practice. Simulation and modeling tools and techniques are most important in this day and age. While simulation carries the needed work, tools for visualizing the results help in the decision-making process. Simulation ranges from a simple queue to molecular dynamics, including seismic reliability analysis, structural integrity assessment, games, reliability engineering, and system safety. This book will introduce practitioners, researchers, and novice users to simulation and modeling, and to the world of imagination

Petri Net Models Optimized for Simulation

Petri nets and simulation are a modeling paradigm and a tool, respectively, which may be successfully combined for diverse applications, such as performance evaluation, decision support, or training on complex systems. Simulation may require significant computer resources; hence, in this chapter, two Petri net-based formalisms are analyzed for profiting from their respective advantages for modeling, simulation, and decision-making support: a set of alternative Petri nets and a compound Petri net. These formalisms, as well as the transformation algorithms between them, are detailed and an illustrative example is provided. Among the main advantages of these formalisms, their intuitive application for modeling discrete event systems in the process of being designed, as well as the compactness that may present the resulting model, in the case of a compound Petri net, leading to efficient decision making, can be mentioned

Modeling and Analysis of Resource Sharing Approach in Common Platform Strategy Using Petri Net Theory

The most competitive advantages in business and manufacturing is resource-sharing.We must share common resources to produce a group of product family with using common platform strategy. This strategy helps us to increase profit and value in business. It is necessary to apply this strategy to model and analyze resource achievability in different situations. In this paper we try to develop a practical model for analyzing common resource behavioral in platform area with using Petri net theory. Petri Nets have been successfully used for modeling and control the dynamics of flexible manufacturing systems.This paper presents some important concepts about common platform and petri net theory and then presents numerical examples to show how to use Petri net for modeling and analysis in common platform. This model is very useful for common platform strategy and can be used to determine reliability of common platform systems in an effective way

Variable grouping in multivariate time series via correlation

The decomposition of high-dimensional multivariate time series (MTS) into a number of low-dimensional MTS is a useful but challenging task because the number of possible dependencies between variables is likely to be huge. This paper is about a systematic study of the “variable groupings” problem in MTS. In particular, we investigate different methods of utilizing the information regarding correlations among MTS variables. This type of method does not appear to have been studied before. In all, 15 methods are suggested and applied to six datasets where there are identifiable mixed groupings of MTS variables. This paper describes the general methodology, reports extensive experimental results, and concludes with useful insights on the strength and weakness of this type of grouping metho

Discovering Petri Net Models of Discrete-Event Processes by Computing T-Invariants

International audienceThis paper addresses the problem of discovering a Petri Net (PN) from a long event sequence representing the behavior of discrete-event processes. A method for building a 1-bounded PN able to execute the events sequence S is presented; it is based on determining causality and concurrence relations between events and computing the t-invariants. This novel method determines the structure and the initial marking of an ordinary PN, which reproduces the behavior in S. The algorithms derived from the method are efficient and have been implemented and tested on numerous examples of diverse complexity. Note to Practitioners—Model discovery is useful to perform reverse engineering of ill-known systems. The algorithms proposed in this paper build 1-bounded PN models, which are enough powerful to describe many discrete-event processes from industry. The efficiency of the method allows processing very large sequences. Thus, an automated modeling tool can be developed for dealing with data issued from real systems