🌱 City Pollution Reduction Plan

A Numerical Optimization Project using the Simplex Method

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📘 Project Overview

The City of Greenvale has been mandated by the national government to drastically reduce its pollution footprint within the next year.
The Environmental Commission identified ten priority pollutants that must meet annual reduction targets:

• CO₂ (tons)
• NOₓ (tons)
• SO₂ (tons)
• PM2.5 (tons)
• CH₄ (tons)
• VOC (tons)
• CO (tons)
• NH₃ (tons)
• Black Carbon (BC) (tons)
• N₂O (tons)

To achieve these reductions, Greenvale can select from 30 mitigation options, including renewable energy projects, reforestation, and public transport improvements.
Each option:

• Reduces a unique mix of pollutants.
• Incurs a specific implementation cost.

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🎯 Objective

Determine the optimal number of units for each mitigation option to:

1. Meet or exceed the pollutant reduction targets for all ten pollutants.
2. Minimize the total cost of implementation.

This problem was modeled and solved using Linear Programming via the Simplex Method.

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⚙️ Methodology

1. Model Formulation

   • Decision Variables: Units of each mitigation option to implement.
   • Objective Function: Minimize total cost.
   • Constraints: Achieve or surpass target reductions for each pollutant.

2. Solution Approach

   • Used the Simplex Method to solve the linear optimization problem.
   • Conducted data preprocessing and matrix setup using NumPy and Pandas.
   • Built an interactive interface for visualization and parameter adjustment using Streamlit.

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🧠 Tech Stack

Tool / Library	Purpose
Python	Core programming language
NumPy	Matrix and numerical computations
Pandas	Data manipulation and structuring
Streamlit	Web-based interactive user interface

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💡 Example Features

• Adjustable pollutant targets and cost coefficients.
• Visual summary of pollutant reductions achieved.
• Optimal solution table showing cost-minimized implementation plan.
• Real-time solver display using the Simplex algorithm.

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🧾 Course Information

Course: Numerical and Symbolic Computation
Project Title: City Pollution Reduction Plan
Method Used: Simplex Method
Student Numer : 2024-*****

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🚀 How to Run

1. Clone the repository:

   git clone https://github.com/Fylows/simplex-project
   cd simplex-project

2. install dependencies

   pip install -r requirements.txt

3. Run the streamlitapp

   streamlit run Solver.py
   
   

📊 Results

The model provides:

1. The minimum total cost required to meet all reduction targets.
2. The optimal allocation of mitigation options.
3. Insights into trade-offs between pollutant reduction and expenditure.

🏆 Developed as part of my Numerical and Symbolic Computation Course.