Practical Work @ Decision Modelling 👨🏻‍💻

Table of contents

• Introduction
• About the course
  • Main Topics
• Labs
  • Lab 01 - Testing Binary Relations
  • Lab 02 - Binary Relations via Linear Programming
• Setup
  • Create new enviornment
  • Setup pre-commit hooks

1. Introduction

Decision modeling refers to the use of mathematical or scientific methods to determine an allocation of scarce resources which improves or optimizes the performance of a system.

2. About the course

A decision model provides a way to visualize the sequences of events that can occur following alternative decisions (or actions) in a logical framework.

There are two types of decision models in the literature:

1. Deterministic models
2. Probabilistic models

The purpose of this course is to study different ways to model a deterministic decision model.

2.1. Main Topics

• Introduction to Decision Modeling
• Preferences as binary relations
• Voting rules as Group Decision Making Models

3. Labs

The main aim of this repository is to keep track of the work we have done in Decision Modelling (DeM) labs.

3.1. Lab 01 - Testing Binary Relations

In this lab, we focused on testing binary relations (given a matrix/graph to extract binary relations). You could use NetworkX to generate a graph/matrix to test different the binary relations.

Please checkout lab's details here

3.2. Lab 02 - Binary Relations via Linear Programming

This lab focuses on implementing a decision model for some given constraints via linear programming. You could use the following python packages to solve linear programs:

• Linear Programming with Python and PuLP
• scipy.optimize.linprog

For more details: checkout this detailed guidline

Please checkout lab's details here

4. Setup

If you want to follow along with the lab exercises, make sure to clone and cd to the relevant lab's directory:

git clone https://github.com/mohammadzainabbas/DeM-Lab.git
cd DeM-Lab/src/<lab-of-your-choice>

For e.g: if you want to practice lab # 1, then you should do cd DeM-Lab/src/lab1.

4.1. Create new enviornment

Before starting, you may have to create new enviornment for the lab. Kindly, checkout the documentation for creating an new environment.

Once, you have activated your new enviornment, we may have to install all the dependencies for a given lab (kindly check if requirements.txt file exists for a given lab before running the below command):

pip install -r requirements.txt

4.2. Setup pre-commit hooks

In order to setup pre-commit hooks, please refer to the documentation.