Study Of Discrete Event Systems Research Articles

Mathematical Model for Production Plan Optimization—A Case Study of Discrete Event Systems

This paper proposes an optimal scheduling model under production and maintenance constraints for a real case of a discrete event system. The intent was to use the rich mathematical theory and algorithms of optimization in the study of this important class of systems. The current study detailed firstly a new approach for mapping a simulation event relationship graph into a mixed-integer program, with a flexible workshop real case. Several other potential applications of the mathematical model are examined, thanks to the model constraints flexibility characteristics, including a general case of a manufacturing system for optimal resource scheduling, an application on the case of hospital beds’ management. The model extension could be also interesting for other applications like museum systems or the case of big data in complex and social networks.

On the index of convergence of a class of Boolean matrices with structural properties

ABSTRACT Boolean matrices are of prime importance in the study of discrete event systems (DES), which allow us to model systems across a variety of applications. The index of convergence (i.e. the number of distinct powers of a Boolean matrix) is a crucial characteristic in that it assesses the transient behaviour of the system until reaching a periodic course. In this paper, adopting a graph-theoretic approach, we present bounds for the index of convergence of Boolean matrices for a diverse class of systems, with a certain decomposition. The presented bounds are an extension of the bound on irreducible Boolean matrices, and we provide non-trivial bounds that were unknown for classes of systems. Furthermore, the proposed method is able to determine the bounds in polynomial time. Lastly, we illustrate how the new bounds compare with the previously known bounds and we show their effectiveness in cases such as the benchmark IEEE 5-bus power system.

Tolerance types of interval eigenvectors in max-plus algebra

Max-plus algebra plays a key role in the study of discrete event systems in connection with optimization problems such as scheduling or project management in which the objective function depends on the operations maximum and plus. The steady states of such systems correspond to the eigenvectors of max-plus matrices, therefore the investigation of the properties of these eigenvectors is important for applications.Matrices and vectors with interval coefficients in a max-plus algebra are studied in this paper, and polynomial algorithms are presented for the recognition problem with three types of tolerance interval eigenvector.

Modeling and Performance Evaluation of Inventory Systems Using Batch Deterministic and Stochastic Petri Nets

This paper presents our work on modeling and performance analysis of inventory systems using batch deterministic and stochastic Petri nets (BDSPNs). It addresses issues frequently raised by industrial companies, but did not receive enough attention by the Petri nets (PNs) community in spite of its important role in the study of discrete event systems. The BDSPN is a new class of PNs capable of describing the synchronization of discrete and batch token flows in discrete batch processes. Such processes appear in inventory systems or more general supply chains where materials are purchased in finite discrete quantities (batches of different sizes), and many operations such as inventory replenishment and customer order fulfillment are usually performed in a batch way because of the batch nature of customer orders and/or in order to take advantages of the economies of scale. In this paper, the BDSPN model is formally introduced, and its conflict resolutions of transitions and batch firing indexes are addressed. The model is then applied to the modeling and performance evaluation of various inventory systems. Analytic performance evaluation techniques are developed for the model with illustrative applications to the inventory systems. Our study shows that the model is powerful for both modeling and performance evaluation of the systems.

Monotonicity and positive invariance of linear systems over dioids

In this paper, we make connections between two apparently different concepts. The first concept is the (linear) monotonicity of a given matrix which is usually used in order to compare Markov chains. This concept is involved in the simplification of complex stochastic systems in order to control the approximation error made. The second concept is the positive invariance of sets by a (linear) map. The properties of positively invariant sets are involved in many different problems in classical control theory, such as constrained control, robustness analysis, optimisation, and also in aggregation of Markov chains (namely strong lumpability and coherency). In the context of linear dynamical systems over semirings which play an important role in the study of discrete event systems, we establish links between monotone (or isotone) linear maps and linear maps which admit some special families of positively invariant sets.

The limits of extended Kalman filtering for pulse train deinterleaving

Some signals are transmitted as periodic pulse trains. If more than one pulse train is transmitted over the same communication channel, a challenge is to separate them for source identification at the receiver. This is known as pulse train deinterleaving and is clearly a fundamental problem in the study of discrete-event systems. Frequently, the only relevant information at the receiver is the time of arrival (TOA) data, which is usually contaminated by jitter noise. Perhaps there are also missing or overlapping pulses. In this paper, we present an approach for deinterleaving pulse trains and estimating their periods using an extended Kalman filter (EKF). A naive application of EKF theory is not attractive because of discontinuities in the signal model. Here, a form of smoothing of the discontinuities is proposed so that the EKF approach becomes attractive. The advantage of this EKF approach is that it is less computationally expensive than most previously proposed methods, which are of order N/sup 2/, where N is the number of pulses being processed. The computation required here is of order N. The method proposed appears to give useful results for up to seven or so pulse trains, particularly when there is some a priori information on the pulse frequencies, which can be obtained using computations of order N log N.

A GSMP formalism for discrete event systems

A precise mathematical framework for the study of discrete event systems is described. The idea is to define a particular type of stochastic process, called a generalized semi-Markov process (GSMP), which captures the essential dynamical structure of a discrete event system. An attempt is also made to give the flavor of the qualitative theory and numerical algorithms that can be obtained as a result of viewing discrete event systems as GSMPs. Likelihood ratio concepts for importance sampling are briefly described.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>