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The goal of the vehicle routing problem (VRP) is to identify an optimal set of routes for a fleet of vehicles visiting multiple delivery locations. The changing economic and geopolitical scenario has made last-mile delivery one of the most challenging and expensive tasks of the logistics fulfillment cycle. In this hands-on lab, we'll provide a brief introduction to VRP and help you learn how to create a real-time fleet routing workflow using GPU-accelerated heuristics, metaheuristics, and optimization solvers. We'll use RAPIDS, GPU-accelerated Python libraries to load and preprocess the data, and cuOpt, a Python-based optimization API, to solve a real-world supply chain problem.
Prerequisite(s):
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