By Stewart Robinson, Roger Brooks, Kathy Kotiadis, Durk-Jouke Van Der Zee

Bringing jointly a world staff of researchers focused on army, enterprise, and well-being modeling and simulation, Conceptual Modeling for Discrete-Event Simulation offers a finished view of the present cutting-edge within the box. The e-book addresses a number of matters, together with: what's a conceptual version? How is conceptual modeling played more often than not and in particular modeling domain names? what's the position of proven methods in conceptual modeling? all the book’s six components specializes in a unique point of conceptual modeling for simulation. the 1st part discusses the aim and standards of a conceptual version. the following set of chapters offers frameworks and instruments for conceptual modeling. The publication then describes using tender platforms method for version structuring in addition to the appliance of software program engineering equipment and instruments for version specification. After illustrating how conceptual modeling is followed within the army and semiconductor production, the ebook concludes with a dialogue on destiny examine instructions. This quantity deals a wide, multifaceted account of the sphere by means of featuring varied views on what conceptual modeling involves. It additionally offers a foundation upon which those views will be in comparison.

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The step of problem formulation consists of understanding the problem and setting the scope and objectives for the project. There is no agreed definition of conceptual modeling within simulation and operational research (OR) and, for example, setting the project objectives is sometimes included as part of conceptual modeling (Robinson 2008). This chapter examines how the choice of model and the comparison of alternative models has been discussed and investigated in the literature. It includes both mathematical and simulation models from a range of applications in different areas of science, on the basis that in each case the underlying modeling problem is similar—deciding what to include in the model to produce the best outcome for the project.

Meanwhile, Arthur and Nance (2007) identify the potential to adopt software requirements engineering (SRE) approaches for simulation model development. They also note that there is little evidence of SRE actually being adopted by simulation modelers. Pace (1999, 2000a) explores a four-stage approach to conceptual model development, similar to that of Shannon: collect authoritative information on the problem domain; identify entities and processes that need to be represented; identify simulation elements; and identify relationships between the simulation elements.

An assessment of model performance requires a measurement to be made of each of the performance elements and this is far from straightforward. It should be possible to evaluate elements 1, 6, 9, and 11 fairly easily in most cases, although care is required in the interpretation of the measures used. However, the remaining elements are hard to quantify and a subjective qualitative assessment may be all that is be possible. The accuracy of the results (element 2) may not be known until a long time after the project was completed and may never be known for decision scenarios that were not implemented.

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