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    <title>Version [2.0] — [pyMCMA: Uniformly distributed Pareto-front representation]</title>
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    <keywords>Pareto-front representation, Multiple-criteria model analysis, Pareto-front visualization, Clustering, Pyomo modeling language, Structured modeling</keywords>
    <abstract>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 the distances between neighbor Pareto solutions. pyMCMA supports scientific, i.e., objective, model analysis by providing preference-free Pareto front representation.
The update provides new functionalities and enhancements. The former include clustering of the Pareto-front solutions. The enhancements include internal software improvements, optional customization of some parameters, as well as a new functionalities that might be used by advanced users.</abstract>
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