Simulated Annealing Project

This repository contains several implementations of the Simulated Annealing (SA) metaheuristic applied to different optimization problems. The project is written in C++.

The implemented problems include:

1. Benchmark function optimization **
2. 0/1 Knapsack Problem
3. Traveling Salesman Problem (TSP)
4. Vehicle Routing Problem with Time Windows (VRPTW)

** This is not our focus but it put anyways :)

Table of Contents

• Project Description
• Repository Structure
• Simulated Annealing Overview
• Implemented Problems
  • 1. Benchmark Function Optimization
  • 2. Knapsack Problem
  • 3. Traveling Salesman Problem
  • 4. Vehicle Routing Problem with Time Windows

---

Project Description

The goal of this project is to study and implement the Simulated Annealing algorithm as a general optimization method. SA is inspired by the physical annealing process, where a material is heated and then slowly cooled to reach a stable low-energy configuration.

In optimization, the algorithm explores the solution search space by accepting better solutions and, with a certain probability, also accepting worse solutions. This allows the algorithm to escape local optima and continue searching for better global solutions.

This project applies Simulated Annealing to both:

• Maximization problems, such as the Knapsack Problem.
• Minimization problems, such as the Traveling Salesman Problem and the Vehicle Routing Problem with Time Windows.

---

Repository Structure

SimulatedAnnealingProject/
│
├── EvaluatingBechmarkFunctions/
│   ├── SAmain.cpp
│   └── SAmain.exe
│
├── KanaspackProblem/
│   ├── dataset/
│   ├── kp.cpp
│   ├── kp.exe
│   ├── objective_history.csv
│   ├── objective_weight_history.csv
│   └── value_weight_history.csv
│
├── TravelingSalesmanProblem/
│   ├── dataset/
│   │   └── d2/
│   ├── TSP.cpp
│   ├── TSP.exe
│   ├── TSPTesting.cpp
│   └── TSPTesting.exe
│
├── VRPTW/
│   ├── dataset/
│   ├── VRPTW.cpp
│   └── VRPTW.exe
│
└── README.md