Environmental Sustainable Fleet Planning in B2C e-Commerce Urban Distribution NetworksSmart City

Sustainable distribution is one of the topics concerning the smart city concept. In this chapter we face the problem of delivering a given amount of goods in urban areas arising from e-channel department stores, with the aim of minimizing the overall distribution costs; costs take into account traveling components, loading and other operative aspects, and environmental issues. More precisely, in the present business to consumer distribution problem, we have to determine the fleet of not homogeneous vehicles (trucks, wagons, vans and picks-up) to be used for satisfying the demands of clients coming from e-channels, and their related itineraries, given the traveling limits imposed by the urban government; in particular, we have to respect the maximum route length constraints and use the appropriate vehicles for each kind of street. We propose a mathematical programming model to solve this computationally difficult problem, which is strategic for being able to implement sustainable distribution plans in a smart city context. Preliminary results of test bed cases related to different sized urban distribution networks are reported and analyzed

A Time-Dependent No-Overlap Constraint: Application to Urban Delivery Problems

International audienceThe Time-Dependent Traveling Salesman Problem (TDTSP)is the extended version of the TSP where arc costs depend on the timewhen the arc is traveled. When we consider urban deliveries, travel timesvary considerably during the day and optimizing a delivery tour comesdown to solving an instance of the TDTSP. In this paper we presenta global constraint, extended from the no-overlap constraint, that integratestime-dependent transition costs and we compare the performanceof CP models for the TDTSP with and without the new constraint

State-of-the art of freight forecast modeling: lessons learned and the road ahead

Freight demand models, Commodity flow, Truck tours, Supply chain, Logistics, Activity-based, Disaggregate,