📘 Evolutionary Computing & Fuzzy Logic – MATLAB Implementation

By Sahil Dastagir Mujawar

This repository contains my complete implementation of Differential Evolution, Genetic Algorithms, and Fuzzy Logic systems in MATLAB.
The project demonstrates optimization techniques, multi-run analysis, visualization, and rule-based fuzzy inference — developed as part of my MSc Artificial Intelligence coursework at De Montfort University.

📁 Repository Structure

Evolutionary-Computing-and-Fuzzy-Logic-Sahil/
│
├── Differential_Evolution/
│   ├── de.m
│   ├── Sphere.m
│   └── Rosenbrock.m
│
├── Genetic_Algorithm/
│   ├── RunGA.m
│   ├── RunMultipleTimes.m
│   ├── SelectionFunction.m
│   ├── TournamentSelection.m
│   ├── RankSelection.m
│   ├── RouletteWheelSelection.m
│   ├── Crossover.m
│   ├── Mutation.m
│   ├── SortPopulation.m
│   ├── RosenbrockFunction.m
│   ├── FullPipeline.m
│   ├── ComputeFinalStatistics.m
│   └── FinalStatistics.m
│
├── Fuzzy_Logic/
│   └── fuzzy_logic.m
│
└── Results/
    ├── Run1_SideBySide.png
    ├── Run2_SideBySide.png
    ├── Run3_SideBySide.png
    ├── Run4_SideBySide.png
    ├── Run5_SideBySide.png
    ├── Run6_SideBySide.png
    ├── Run7_SideBySide.png
    ├── Run8_SideBySide.png
    ├── Run9_SideBySide.png
    ├── Run10_SideBySide.png
    ├── Run11_SideBySide.png
    ├── Run12_SideBySide.png
    ├── Run13_SideBySide.png
    ├── Run14_SideBySide.png
    ├── Run15_SideBySide.png
    ├── Run16_SideBySide.png
    ├── Run17_SideBySide.png
    ├── Run18_SideBySide.png
    ├── Run19_SideBySide.png
    ├── Run20_SideBySide.png
    ├── results_A.txt
    ├── results_B.txt
    └── results_C.txt

🚀 Project Overview

🔹 1. Differential Evolution (DE)

Includes:

• Mutation operator
• Recombination
• Fitness evaluation
• Sphere & Rosenbrock functions

🔹 2. Real-Coded Genetic Algorithm (GA)

Includes:

• Tournament Selection
• Rank & Roulette Selection
• Uniform Crossover
• Mutation
• Multi-run analysis (RunMultipleTimes.m)
• Automated plots

🔹 3. Fuzzy Logic System

Includes:

• Membership functions
• Fuzzification
• Rule evaluation
• Defuzzification
• Visualization

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📊 Results & Visualization

The Results folder contains:

• 20+ side-by-side comparison plots
• Final fitness statistics
• Convergence behavior analysis

Example visualization:

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▶️ How to Run

1. Open MATLAB
2. Navigate to this folder
3. Run GA:

   RunGA
   

🛠️ Tools Used

MATLAB R2023b

Differential Evolution

Real-Coded Genetic Algorithm

Custom fuzzy logic system

🎯 Key Learnings

Implementing evolutionary algorithms

Designing selection, crossover, mutation strategies

Multi-run statistical evaluation

Optimization visualization

Fuzzy logic system design

Writing modular MATLAB code

📬 Contact

Sahil Dastagir Mujawar 📍 Leicester, UK 🔗 LinkedIn: https://www.linkedin.com/in/sahil-mujawar-75a484200

🔗 GitHub: https://github.com/SahilMujawar03

Feel free to explore and connect!