Hey everyone! I'm currently participating in a hackathon where our task is to efficiently distribute 20,000 orders among 200 couriers. We've been considering training a neural network to identify various delivery routes, but we realized that we might not complete it within the two-week deadline. Instead, we're thinking of creating a hybrid machine learning model combined with an algorithm. We initially looked into Mixed-Integer Linear Programming (MILP), but it's quite greedy, and we're searching for alternative suggestions. What algorithms do you recommend for this scenario?
4 Answers
Using tools like Google is a great idea if you can; they have solid optimization solutions that might help streamline your project.
Try looking into Google's optimization tools; they have guides and pre-trained models specifically for routing problems. It could save you a ton of time! Here's the link: developers.google.com/optimization/routing/vero.
I suggest checking out the Vroom and OSRM libraries; they're known to work well for routing problems like yours. They might suit your hackathon needs perfectly!
Given the parameters of your problem, you could even throw a Support Vector Machine at it for a straightforward solution.
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