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This repository seeks to optimize bikes distribution of a public bicycle renting service across city stations using local search algorithms like Hill Climbing and Simulated Annealing, aiming to minimize costs and efficiently meet demand. It includes tools to visualize the distribution and showcases the utility of AI in urban logistics.
caiselvas/bicing-optimization-local-search
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This repository seeks to optimize bikes distribution of a public bicycle renting service across city stations using local search algorithms like Hill Climbing and Simulated Annealing, aiming to minimize costs and efficiently meet demand. It includes tools to visualize the distribution and showcases the utility of AI in urban logistics.
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