General Morphological Analysis
(Redirected from Morphological analysis (problem-solving))
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A General Morphological Analysis is a Problem Solving Task that examines all possible solutions to a multidimentional non-quantified complex problem.
- AKA: Morphological Analysis (Problem-Solving), GMA.
- See: Fritz Zwicky, Zwicky Box, Typology Analysis.
References
2019
- (Wikipedia, 2019) ⇒ https://en.wikipedia.org/wiki/Morphological_analysis_(problem-solving) Retrieved:2019-1-26.
- Morphological analysis or general morphological analysis is a method developed by Fritz Zwicky (1967, 1969) for exploring all the possible solutions to a multi-dimensional, non-quantified complex problem.[1]
- ↑ Ritchey, T. (1998). General Morphological Analysis: A general method for non-quantified modeling.
2002
- (Ritchey,2002) ⇒ Tom Ritchey (2002). "General Morphological Analysis: A general method for non-quantified modelling".
- QUOTE: Essentially, general morphological analysis is a method for identifying and investigating the total set of possible relationships or “configurations" contained in a given problem complex. In this sense, it is closely related to typology analysis, although GMA is more generalised in form and has far broader applications.
The approach begins by identifying and defining the parameters (or dimensions) of the problem complex to be investigated, and assigning each parameter a range of relevant “values" or conditions. A morphological box - also fittingly known as a “Zwicky box” - is constructed by setting the parameters against each other in an n-dimensional matrix (see Figure 1a). Each cell of the n-dimensional box contains one particular “value” or condition from each of the parameters, and thus marks out a particular state or configuration of the problem complex.
- QUOTE: Essentially, general morphological analysis is a method for identifying and investigating the total set of possible relationships or “configurations" contained in a given problem complex. In this sense, it is closely related to typology analysis, although GMA is more generalised in form and has far broader applications.