This paper deals with a tutorial study of applied system simulation. We present the applications of system simulation, simulation types, and elaborate on discrete-event simulation, DES. Then we explain the level of details needed in a simulation model. We investigate the signi®cance of simulation experiments and explain in detail the standard methodology used in the development of a simulation ...

We develop a way of simulating disease spread in networks faster at the cost of some accuracy. Instead of a discrete event simulation (DES) we use a discrete time simulation. This aggregates events into time periods. We prove a bound on the accuracy attained. We also discuss the choice of step size and do an analytical comparison of the computational costs. Our error bound concept comes from th...

Discrete-event simulation based optimization is the process of finding the optimum design of a stochastic system when the performance measure(s) could only be estimated via simulation. Randomness in simulation outputs often challenges the correct selection of the optimum. We propose an algorithm that merges Ranking and Selection procedures with a large class of random search methods for continu...

This chapter deals with modelling and control of discrete event systems. Discrete event systems (DES) are event driven man made systems whose evolution is guided by occurrences of asynchronous events as opposed to classical time driven discrete or continuous systems. DES are modelled by tools from computer science like automata, Petri nets and process algebras. There are two major streams in co...

Hybrid control systems, that is, systems which contain both continuous dynamics and discrete event dynamics are studied in this paper. First, a model is introduced that describes the continuous plant and discrete event controller along with an interface which connects them. A Discrete Event System (DES) automaton description is employed to describe the plant together with the interface and it i...

The modelling and simulation of sophisticated technical systems is a demanding task. On the one hand, the physical part consists of a large number of subsystems which exhibit predominantly continuous dynamics, sometimes with (infrequent) discontinuities. On the other hand, the distributed computerised control systems constitute complex discretetime and discrete-event systems that require comple...

This paper is the first of its type in that it provides an empirical study comparing the two simulation approaches of Discrete-Event Simulation (DES) and System Dynamics (SD). Prior comparison work is limited and mostly based on the authors‟ personal opinions. In the present work the comparison is based on managers‟ (executive MBA students) perceptions of two simulation models of the same probl...

Simulation is a common tool for modeling and evaluating real-life systems. In discrete event simulation (DES) a system is represented from the perspective of its events. Modern tools for developing simulations are bound to general purpose programming concepts that cannot represent the simulation domain effectively. In this paper, we propose a model-driven approach to DES domain. We provide a me...

Conceptual Modeling (CM) is a fundamental step in a simulation project. Nevertheless, it is only recently that structured approaches towards the definition and formulation of conceptual models have gained importance in the Discrete Event Simulation (DES) community. As a consequence, frameworks and guidelines for applying CM to DES have emerged and discussion of CM for DES is increasing. However...

A structural decentralised control of discrete-event system (DES) is employed for a simulation study of a sequence control of cleaning-in-process of chemical batch plant. Due to the number of states of the whole plant model is too big, the whole plant has subdivided into smaller sizes and in the local level, the DES models for the local plant and local specifications are established. The condit...