Capacitated Vehicle Routing Problem with Machine Learning

This repository is the part 2 for CVRP-GA.

This repository contains algorithms to solve the CVRP (Capacitated Vehicle Routing Problem) in C++ and incorporating Machine Learning (ML) from python

Algorithms:

1. Genetic Algorithm (GA)
2. Genetic Algorithm (GA) - Machine Learning (ML)

To build and run:

git clone https://github.com/sakshisingh1809/CVRP-with-GA.git  
cd cvrp
mkdir build  
cd build
cmake .. && make -j4
./cvrp  

Table of contents:

• Algorithms
• Instructions
• Table of contents
• Code Overview
• Notes

Code Overview:

1. The code contains Problem, Solution and Vehicle classes. Each algorithm implementation has its own class and inherits the Solution class.
2. The problem is setup using the Problem class which specifies the number of nodes (centres/dropoff points), maximum demand, number of vehicles, their capacity, the grid range and the type of distribution. The demand for each centre as well as its location is randomly generated.
3. A base class called Solution has been created to store the basic elements of the solution in a user friendly format. This includes a vector of instances of the Vehicle class.
4. The Vehicle class stores the vehicle id, the route it takes, the total capacity, the number of units still left in the vehicle, and the cost associated with the vehicle's route. The << operator is overloaded to show the status of the node and vehicle respectively. PrintVehicleRoute() prints only the route of the vehicle.
5. The Solution class also contains a virtual method called Solve(). Each algorithm class overrides the Solve() method.
6. The Solution class also contains a method called PrintSolution(option) with the an input option (option) to print vehicles' statuses or routes in addition to the total cost and validity of the solution.

Notes:

1. The documentation for private functions (such as operators in the GASolution class) has been made available to aid understanding.
2. Custom hybrid algorithms, that involve feeding in the solution of 1 algorithm to another can easily be implemented, as the structure allows the extraction of solution from the algorithm classes. An example is shown at the end of main.cpp.