This project presents a sophisticated solution to the Vehicle and drone Routing Problem with Pickup and Loading (VRPPL) using the Pulp library and the Gurobi optimizer. The objective is to optimize the distribution of packages across various nodes, efficiently planning routes for a fleet of vehicles with the combination of a drone. Our approach not only minimizes travel cost and time but also respects loading constraints, ensuring a realistic and practical application.
By integrating cutting-edge operations research techniques and powerful optimization tools, the model strategically addresses the complexities involved in real-world logistics and distribution systems. This project serves as a valuable resource for anyone looking to understand or improve upon route optimization and logistics planning.
- Optimization of Package Distribution: Efficiently determine the best routes for delivering packages across various nodes.
- Minimization of Travel Cost and Time: Utilize algorithms that reduce overall travel time and associated costs, leading to more efficient distribution.
- Respect for Loading Constraints: Ensure that vehicle loading constraints are met, providing solutions that are feasible in practical scenarios.
- Integration of Advanced Techniques: Leverage powerful libraries like Pulp and optimization solvers such as Gurobi to handle complex optimization tasks effectively.