The developed project tackles the Vehicle Routing Problem for real-case scenarios. Considering a realistic logistics problem for which a company, interested in deploying electric vehicles with the purpose of loading and unloading various goods in a metropolitan area (in this case, Milan), questions how to optimize the usage of its fleet, the present work analyzes real-time data answering in manners of times. The proposed solution revolves around the exploitation of Google APIs in order to fetch data that reflects the real world. Information is used to tune a model with the goal of minimizing the time required to visit all the different clients. The result is first presented numerically through the solution proposed by CPLEX library implemented in Python. Human readable graphics help in this task, showing the chosen routes that the vehicles will make.
yksop/Digital-production-and-logistics-systems-Project-Module-2
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