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This project is a new knee point identification method for posteriori decision-making.

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JerryI00/KPI

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Installation

  • Python version should be 3.6
  • Install thrid-party packages (In Anacaonda environment)
    • pip install sklearn
    • pip install pandas

A quick start to run experiments

  • Run code\main.py to get files about knee points identified by all six KPI methods. The files are stored by default in code\results after run main.py.
  • Run code\algorithms\KPITU.py to observe the results of KPITU on the specified test problem separately. Other .py files in code\algorithms can be run separately like this to get the corresponding results.

Examples of the search dynamics of KPITU for identifying knee point(s).

  • Problems with only one knee point, such as PMOP1 with A=2 in 2D and 3D:

* Problems with more than one knee point, such as PMOP1 with A=4 in 2D and 3D:

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This project is a new knee point identification method for posteriori decision-making.

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