Model predictive control (MPC) is a very popular controller design method in the process industry. A key advantage of MPC is that it can accommodate constraints on the inputs and outputs. Usually MPC uses linear or nonlinear discrete-time models. In this paper and its companion paper (“Part II: Hybrid Systems”) we give an overview of some results in connection with MPC approaches for discrete-e...

Insurance companies are among the service organizations, which maintain close relationships with their clients by providing insurance services. Clients are the most important resource for service companies. And profitability of insurance companies undoubtedly hinges on clear analysis of client satisfaction and improved productivity of service providers. An important factor of client satisfactio...

This article proposes an approach to a hybrid software process simulation modeling (SPSM) using discrete event system specification (DEVS) formalism, which implements the dynamic structure and discrete characteristics of the software development process. Many previous researchers on hybrid SPSM have described both discrete and continuous aspects of the software development process to provide mo...

The work performed by the authors to provide to Modelica more discrete-event system modeling functionalities is presented. These functionalities include the replication of the modeling capacities found in the Arena environment, the SIMAN language and the DEVS formalism. The implementation of these new functionalities is included in three free Modelica libraries called ARENALib, SIMANLib and DEV...

this article proposes composition of fuzzy sets theory with discrete-event simulation and puts it into application in order to model uncertain activity duration in simulating a real-world system. the purpose of this paper is to assess the usefulness of fuzzy simulation for modeling uncertain activity duration, especially when insufficient or no sample data is available. in this research, fuzzy ...

Agent-based simulations of pedestrian crowd behavior include a large number of agents, each of which typically decides its movement behavior in a time-based manner. Such a time-based approach makes it difficult to exploit the crowd system’s spatial and temporal heterogeneity resulting from agents’ non-uniform movements. This paper presents a discrete event approach for simulating pedestrian cro...

Especially suitable for the modeling and simulation of technical systems in a wider sense, discreteevent simulation is one of the most important and most versatile tools of the craft. Both students and practitioners should be familiar with its principles and mechanics, in particular if they are interested to look beyond their favorite modeling tool’s GUI. This paper presents a short tutorial on...

since the analysis of complex services systems by using mathematical modeling techniques, with considering the random patterns prevailing in them, is so difficult or probably impossible, improvement guidelines are often followed based on the experts' experiences using qualitative methods. in the present paper, by employing a discrete event computer simulation methodology, criminal trial sy...

In discrete event systems event times are often correlated among events of one event stream and also between different event streams. If this correlation is neglected, then resulting simulation models do not describe the real behavior in a sufficiently accurate way. In most input modeling approaches, no correlation or at most the autocorrelation of one event stream is considered, correlation be...