Investment Optimisation

About

A Python script that solves an investment optimization problem. It explores all possible combinations of actions to determine the best investment strategy while adhering to budget constraints.

Features

• Search for the best combination of actions to maximize profit.
• Adherence to budget constraints.
• Ability to specify a CSV file containing action data.
• Brute-force algorithm to explore all possible combinations.
• Optimized algorithm to go way faster

Usage

1. Ensure you have Python installed on your system.
2. Download the source code from the GitHub repository:

bash git clone https://github.com/Tuxiboule/Projet7.git

3. Install dependencies if necessary

pip install -r requirements.txt

• Make sure you have a CSV file containing action data. The file should have the following format :

Action #, Cost per Action (in euros), Profit (after 2 years)
1,20,5
2,30,10

• Run the program using the following command :

python bruteforce.py or python optimized.py

Context - Use Python to resolve problem with algorithm

• I really enjoyed this project about optimization.
• The brute-force solution quickly became apparent to me. However, I had to research the optimized solution, which allowed me to learn more about linear optimization problems.

Skills

• Bruteforce

  • CSV Reading
  • Itertools library
  • Optimisation algorithms

• Optimized

  • Using PuLP (Linear Programming)
  • Modeling Optimization Problems

Credits

Tuxiboule