Description
What would you like to Propose?
An algorithm that generates optimized routes for N vehicles, ensuring that each vehicle receives a list of assigned passengers based on:
Vehicle capacity (if applicable)
Passenger coordinates
Optimized sequential allocation
The algorithm should efficiently categorize a given number of passengers into vehicle-specific lists while minimizing travel distance and ensuring balanced distribution.
Issue details
Currently, there is no built-in vehicle routing algorithm in this project that can distribute passengers among vehicles while considering capacity constraints. This feature would significantly improve efficiency for use cases such as employee transport, logistics, or ride-sharing applications.
Describe the solution you'd like
Implement a VRP (Vehicle Routing Problem) algorithm that supports:
Capacity constraints (optional)
Optimized route planning
Efficient passenger allocation
Scalability for large datasets
Preferably use heuristic/metaheuristic approaches such as:
Greedy algorithms
Genetic algorithms
Simulated annealing
Dijkstra’s algorithm for shortest paths
Describe alternatives you’ve considered
Some external libraries (e.g., Google OR-Tools) provide VRP solutions, but an in-house implementation would allow greater flexibility and customization for specific project needs.
Additional context
This feature is beneficial for projects involving fleet management, delivery services, public transportation, and ride-sharing applications.
Open to discussions on preferred optimization techniques!
Additional Information
Acceptance Criteria
✅ Algorithm effectively groups passengers into vehicles while considering capacity (if applicable).
✅ Optimized routes with minimal travel distance.
✅ Scalable and efficient for handling large numbers of passengers and vehicles.
✅ Well-documented and easy to integrate into existing systems.