This MATLAB code (implemented in 2011) provides solutions to the VRP using various optimization algorithms including bee colony algorithm, simulated annealing algorithm, genetic algorithm, tabu search algorithm, and particle swarm optimization algorithm.
The Vehicle Routing Problem (VRP) is a combinatorial optimization and integer programming problem that seeks to determine the optimal set of routes for a fleet of vehicles to traverse in order to deliver goods to a given set of customers. It generalizes the Travelling Salesman Problem (TSP) and has applications in various fields such as logistics and transportation. For more information about the Vehicle Routing Problem, refer to: https://en.wikipedia.org/wiki/Vehicle_routing_problem
To run each solution, execute the corresponding MATLAB file:
- For the Bee Colony Algorithm: run 'beeColony.m'
- For the Simulated Annealing Algorithm: run 'sa.m'
- For the Genetic Algorithm: run 'ga.m'
- For the Tabu Search Algorithm: run 'ts.m'
- For the Particle Swarm Optimization Algorithm: run 'pso.m'
Each MATLAB file contains the implementation of the respective algorithm to solve the VRP. Additional parameters or configurations can be adjusted within the MATLAB files if needed.
Contributions to improve the code or add new algorithms are welcome. If you encounter any issues or have suggestions for improvements, please feel free to open an issue or submit a pull request on GitHub.