Cost of transportation of goods and services is an interesting topic in today's society. Capacitated vehicle routing problem is one of the variants of the vehicle routing problem. In this research we develop a machine learning technique to nd optimal paths from a depot to the set of customers while also considering the capacity of the vehicles, in order to reduce the cost of transportation of goods and services. Each vehicle originates from a depot, service the customers and return to the depot. We compare the machine learning model with an exact method; column generation. Our objective is to solve a large-size of vehicle routing problem to optimality.

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