| Autor: |
Marek Makowski, Janusz Granat, Andrii Shekhovtsov, Zbigniew Nahorski, Jinyang Zhao |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
SoftwareX, Vol 27, Iss , Pp 101801- (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2352-7110 |
| DOI: |
10.1016/j.softx.2024.101801 |
| Popis: |
pyMCMA is the Python implementation of a novel method for autonomous computation of the Pareto-front representation composed of efficient solutions distributed uniformly in terms of distances between neighbor Pareto solutions. pyMCMA supports scientific, i.e. objective, model analysis by providing preference-free Pareto front representation. pyMCMA seamlessly integrates independently developed substantive models. The computed Pareto-front, also for more than two criteria, is visualized by interactive parallel coordinate plot, as well as by charts of criteria pairs. Moreover, pyMCMA optionally exports the results for problems-specific analysis in the substantive model’s variables space. The pyMCMA functionality is illustrated by an analysis of China’s liquid fuel production model. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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