We present on the one hand, the architecture of modelling environment and on the other hand, the logical models of the proposed data warehouse.
The proposed optimization model was implemented on a PC with Dual Xeon Quad Core 2.5 GHz processor and 4 GB RAM using ILO Gs OPL Studio 6.1.1 as the modelling environment and CPLEX 11.2.1 as solver.
The symbols used in Figure 1 are standard system dynamics notation common to several visual modelling environments (Ford 1999), and are not merely a diagram, but form a model with which simulations may be made.
Based on the results of these studies, a methodology for hybrid modelling environments is introduced and exemplified.
To deal with non-linear μCHP behaviour in linear deterministic modelling environments, mostly constant cost and efficiency parameters are adopted.
This chapter reveals that the patchwork consists largely of system modelling environments; formal system requirements capture, analysis, and traceability tools; architectural modelling, analysis, optimization, and verification environments; simulators and abstract processor models for software validation.
One key advantage of these visual modelling environments is that the diagram is both the model and the simulator, unlike some early applications where system dynamics flowchart was merely documentation about the model (e.g., Kalgraf 1979).
Armed with such networks, it is possible to analyse their dynamics and other properties using tools/ modelling environments such as COPASI (Hoops et al. 2006) (http://www.copasi.org/) and to compare model and experimental data, conveniently stored using SBRML (Dada et al. 2010).
The Network-Oriented Modelling approach is supported by a few modelling environments (in Matlab, or in Python, for example) that can be used to model conceptually in a declarative manner, without the need of programming.
To date there has been little exploration of the opportunities that modelling environments offer in terms of flexible model construction by transplanting components.
