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One of the main issues related to routing problems applied in an urban context with uncertainty related to the transportation costs is how to define realistic instances. In this paper, we overcome this issue, providing a standard methodology to extend routing instances from the literature incorporating real data provided by sensors networks. In order to test the methodology, we consider a routing problem specifically designed for City Logistics and Smart City applications, the multi-path Traveling Salesman Problem with stochastic travel costs, where several paths connect each pair of nodes and each path shows a stochastic travel cost with unknown distribution

The Multi-path Traveling Salesman Problem with Stochastic Travel Costs: Building Realistic Instances for City Logistics Applications