Decision Support Systems – Decision Analysis Project

This repository contains a university project developed for the course Decision Support Systems.
The project applies various decision-making methods under uncertainty and risk, as well as multi-criteria analysis.

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Contents

• main.py – Python code (using pandas, numpy, matplotlib) implementing the decision models.
• results_summary.csv – Summary table including all calculated results.
• decision_tree.png – Visualization of the decision tree.

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Implemented Methods

• Decision under Uncertainty

  • Maximin
  • Maximax
  • Laplace
  • Savage (Minimax Regret)

• Decision under Risk

  • Expected Monetary Value (EMV)
  • Variance
  • Standard Deviation

• Multi-Criteria Decision Making (MCDM)

  • Weighted Sum Model (WSM)

• Decision Tree Visualization

  • Generated with matplotlib and exported as PNG.

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Results Summary

Available in results_summary.csv with criteria such as Maximin, Maximax, Laplace, Savage, EV, Variance, StdDev, and WSM.

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Notes

This project was created as part of a university assignment.

It is intended for educational and research purposes only.