Hey everyone! I'm currently participating in a hackathon where we need to assign 20,000 orders to 200 couriers. Initially, we considered using a neural network to find various routes, but we've realized that with just two weeks left, that might not be feasible. Instead, we're thinking about creating a hybrid machine learning model combined with an algorithm. We thought about using a Mixed-Integer Linear Programming (MILP) approach, but we feel it might be too greedy. What other algorithms could you recommend for efficient routing?
4 Answers
You might want to check out tools like VROOM and OSRM. They work really well for routing problems and could save you some time and effort during the hackathon.
Google has some useful guides and pre-trained solvers for routing optimization. You might want to look into that for quicker solutions, especially since you're pressed for time!
With the number of parameters you mentioned, you might be able to apply a Support Vector Machine (SVM) to tackle your problem effectively. It's a straightforward approach that could fit your needs well!
Have you considered using a Dijkstra variant? I'm curious about how a neural network would fit into your plan. What exactly would you train it on? If you have a distance matrix, maybe unsupervised learning or clustering might be worth exploring.
We have a distance matrix, like {"from":20258,"to":1337,"dist":3492}, so Dijkstra isn't suitable for our case.