Abstract
The discussion in this chapter continues the exploration of fundamental notions initiated in Chap. 1. However, a variety of important details relating to the modelling and simulation process are introduced. These set the stage for the discussions in the chapters that follow. Included here are the key notions of the observation interval, entities, data requirements, constants, parameters and (time) variables. The latter, in turn, includes input, state and output variables. The various phases of the modelling and simulation process are introduced. The essential need for clearly defined project goals for any simulation project is stressed throughout because these goals provide the basis for establishing a variety of key facets of model development, e.g. model granularity, input data requirements and output requirements. The successful completion of any modelling and simulation project can encounter many challenges, and care must be taken to avoid pitfalls. The notions of validation, verification and quality assurance are pertinent in this respect and these notions are explored. The chapter ends with the acknowledgement that modelling and simulation projects typically fall into one of two broad categories; these correspond to the study of discrete event dynamic systems (DEDS) and continuous time dynamic systems (CTDS). The two remaining parts of the book are separately focused on these two domains.
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Notes
- 1.
By way of defining a discrete event dynamic system, we adapt, with minor modification, the definition of an equivalent notion taken from [17]: A discrete event dynamic system is a system that evolves over time in accordance with the abrupt occurrence, at possibly unknown irregular intervals, of events that may or may not have a physical nature.
- 2.
A collection of variables organized as a linear array is called a vector variable. We are using here bold font to indicate vector variables. The number of variables represented is called the dimension of the vector. Sometimes, the actual size of the vector is not germane to the discussion and is omitted.
- 3.
The reader is cautioned not to dismiss the issue with the simplistic and naïve assertion that the goal is to solve the problem!
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Birta, L.G., Arbez, G. (2013). The Modelling and Simulation Process. In: Modelling and Simulation. Simulation Foundations, Methods and Applications. Springer, London. https://doi.org/10.1007/978-1-4471-2783-3_2
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