🧠 Soft Computing Assignments

This repository contains practical implementations, algorithmic demonstrations, and small projects covering core Soft Computing concepts and Metaheuristic Optimization Techniques.

📘 Source: Assignment list transcribed from the official course assignment sheet. All tasks are implemented in simple, well-documented code across multiple programming languages (C/C++/Java/Python).

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📜 Assignment Overview

1. Implement fuzzy set operations using C/C++/Java.
2. Implement fuzzy relational operations using C/C++/Java.
3. Solve a single objective function problem using Grey Wolf Optimization (GWO).
4. Solve a single objective function problem using Crow Search Algorithm (CSA).
5. Simulate the working nature of Ant Colony Optimization (ACO).
6. Implement a basic Neuro-Fuzzy System using scikit-fuzzy or any equivalent tool.
7. Solve a function optimization problem using Genetic Algorithm (GA).
8. Demonstrate selection, crossover, and mutation on a sample population.

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🗂 Repository Structure

soft-computing-assignments/
├─ 01-fuzzy-set-ops/                 # Fuzzy Set Operations (C/C++/Java)
├─ 02-fuzzy-relational-ops/          # Fuzzy Relational Operations (C/C++/Java)
├─ 03-gwo-single-objective/          # Grey Wolf Optimization (Python)
├─ 04-csa-single-objective/          # Crow Search Algorithm (Python)
├─ 05-aco-simulation/                # Ant Colony Optimization Simulation
├─ 06-neuro-fuzzy/                   # Neuro-Fuzzy System using scikit-fuzzy
├─ 07-genetic-algorithm-optimization/ # GA for function optimization
├─ 08-ga-operators-demo/             # GA Operators: Selection, Crossover, Mutation
└─ README.md

Each folder includes:

• Source code (well-commented)
• README.md (explaining algorithm logic, input/output format, and sample runs)
• Screenshots/Graphs (for visualization-based assignments)

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🚀 Getting Started

🔧 Requirements (for Python-based Assignments)

# Optional: Create a virtual environment
python -m venv .venv

# Activate the environment
# Windows
.venv\Scripts\activate
# macOS/Linux
source .venv/bin/activate

# Install dependencies
pip install numpy scipy scikit-fuzzy matplotlib

For C/C++/Java programs, simply compile using your preferred compiler (e.g., gcc, g++, or javac).

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🧠 Learning Outcomes

By completing these assignments, you’ll gain hands-on experience with:

• Fuzzy Logic systems and Neuro-Fuzzy integration
• Swarm Intelligence Algorithms (ACO, GWO, CSA)
• Evolutionary Computing (GA-based optimization)
• Function optimization and simulation using real-world techniques

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📝 Notes

• Ensure all programs are well-commented and properly indented.
• For optimization algorithms, visualize convergence graphs whenever possible.
• You can extend each algorithm with performance comparison metrics later.

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Last updated: November 8, 2025