Investment Optimization Program

Overview

The Investment Optimization Program is designed to assist in making strategic investment decisions. It leverages various algorithms - Brute Force, Glouton (Greedy), and Dynamic Programming - to analyze and select the best combination of stock actions that maximize profit while adhering to a specified budget.

Features

• Data Processing: Loads and cleans stock action data from a CSV file.
• Algorithm Selection: Offers the choice of three distinct algorithms:
  • Brute Force: Exhaustively searches all possible combinations of actions.
  • Glouton (Greedy): Utilizes a greedy approach for quick and effective decision-making.
  • Dynamic Programming: Applies a more sophisticated method to solve the problem efficiently.
• Result Visualization: Displays the best combination of actions, total profit, and investment cost.

How to Use

1. Clone the Repository

git clone https://github.com/kenza12/Projet-7.git
cd Projet-7

2. Set Up Your Environment

• Ensure Python 3 is installed on your system.
• Create a virtual environment:

  python3 -m venv venv

• Activate the virtual environment:

  • On Windows: venv\Scripts\activate
  • On macOS/Linux: source venv/bin/activate

• Install dependencies:

  pip install -r requirements.txt

3. Run the Program

Execute the script with the desired algorithm and data file:

python main.py path/to/your/datafile.csv [algorithms]

Replace [algorithms] with one or more of the following: bruteforce, glouton, dynamic.

4. View Results

The program will output the most profitable combination of actions based on the chosen algorithm.

Dependencies

• Python 3
• Pandas
• Numpy
• tabulate