pyMCMA: Uniformly distributed Pareto-front representation
Marek Makowski, Janusz Granat, Andrii Shekhovtsov, Zbigniew Nahorski, Jinyang Zhao · SoftwareX · 2024
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.