The proposed hybrid algorithm can be extended to solve other variants of the Vehicle Routing Problem by adapting the problem constraints and formulation to accommodate the specific requirements of each variant. For the Vehicle Routing Problem with Time Windows (VRPTW), the algorithm can incorporate time constraints for each customer visit, ensuring that deliveries are made within specified time windows. This can be achieved by modifying the objective function and constraints to include time-related variables and penalties for late deliveries. Additionally, the algorithm can be adjusted to optimize routes based on both distance and time considerations.
For the Multi-Depot Vehicle Routing Problem (MDVRP), the algorithm can be enhanced to handle multiple depots and allocate vehicles efficiently from different starting points. This would involve updating the initial solution generation phase to account for multiple depots and ensuring that each vehicle is assigned to the most suitable depot based on proximity and demand distribution. The route optimization process would need to consider the logistics of servicing customers from different depots while minimizing overall travel distance and time.
By customizing the algorithm to address the unique characteristics of each variant, such as time constraints and multiple depots, the hybrid approach can effectively tackle a broader range of real-world routing challenges beyond the basic Capacitated Vehicle Routing Problem.