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SimDec is context-agnostic and can be used for business applications,<ref>Kozlova, M., Collan, M., & Luukka, P. (2017). Simulation decomposition: New approach for better simulation analysis of multi-variable investment projects.</ref> environmental issues,<ref>Deviatkin, I., Kozlova, M., & Yeomans, J. S. (2021). Simulation decomposition for environmental sustainability: Enhanced decision-making in carbon footprint analysis. Socio-Economic Planning Sciences, 75, 100837.</ref>
<ref>Liu, Y. C., Leifsson, L., Pietrenko-Dabrowska, A., & Koziel, S. (2022). Analysis of Agricultural and Engineering Systems Using Simulation Decomposition. In International Conference on Computational Science (pp. 435-444). Springer, Cham.</ref> as well as in science, engineering, and social domains.
== Method==
SimDec operates on [[Monte Carlo Method | Monte Carlo]] simulation (or measured) data where both output and input values are recorded. At least one thousand observations (or simulated iterations) are generally recommended to preserve the readability of the resulting histograms. An outline of the decomposition algorithm, which is readily available in multiple programming languages,<ref name="Software">Simulation Decomposition GitHub https://github.com/Simulation-Decomposition </ref> proceeds as follows:
# '''Select the input variables for decomposition'''. One can use sensitivity indices (see [[variance-based sensitivity analysis]]) to define the most influential variables for decomposition or choose them manually according to the decision-problem context (for example, only those input variables that the decision-maker has the power to change). Two to three input variables, ordered by decreasing value of their sensitivity indices, usually provide the most meaningful decomposition results.
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==References==
{{reflist|30em}}
== See also ==
[[Sensitivity analysis]]
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