Optimizing EV Charging Stations - A Live Code-Along in Zerve

Learn to build an end-to-end optimization project for EV charging station placement through this interactive code-along workshop. Follow along step-by-step as you model a synthetic city, generate EV charging demand, define optimization objectives, and implement heuristic search algorithms to efficiently place charging stations using Zerve's notebook environment. Discover how to translate real-world planning problems into optimization objectives by constructing weighted distance functions and defining constraints like service radius. Master the implementation and iteration of heuristic optimization methods, including k-medoids-style search, to improve facility placement without relying on packaged solvers. Build and visualize complete optimization workflows that include generating synthetic spatial data, evaluating solutions, and comparing baseline versus optimized layouts. Participate actively in this hands-on session designed for real-time interaction, where you can ask questions and receive guidance from experienced PhD data scientists while gaining practical experience with spatial optimization techniques and data visualization methods.