An exact approach for the grocery delivery problem in urban areas

Abstract

In this paper, we face the problem of delivering a given amount of goods in urban areas in a business-to-consumer (B2C) electronic commerce (EC) environment. This problem can be considered as a particular case of vehicle routing problem. As a novel issue, here we have to determine the fleet of no homogeneous vehicles to be used for satisfying the demands of clients coming from grocery e-channels, and their related itineraries, given the traveling limits imposed by the urban government; in fact, commercial vehicles are not allowed to go everywhere and can travel only in restricted daily time windows, according to their pollution emissions. We have to minimize the overall distribution costs, taking into account traveling components and setup ones, together with operative aspects and environmental issues; customer requirements, vehicle capacity and daily shift constraints have to be satisfied too. We outline the main characteristics of the problem in a B2C EC environment and propose a mixed integer linear programming model to solve this NP-hard problem. Computational results of test bed cases related to different sized transportation networks and delivery demands are presented and analyzed with respect to the fleet of vehicles chosen for satisfying the customer demand and the street traffic limitations. Then, a realistic case study derived from the e-distribution channel of a grocery company of Genoa, Italy, is reported. Considerations about CPU time and optimality gap are also given with the idea of making the proposed model effectively used and solved with any commercial software

VRP in urban areas to optimize costs while mitigating environmental impact

“…The present work originates from and extends the results presented in Carrabs et al. ( 2017 ), where the authors proposed a Mixed Integer Linear Programming (MILP) model for defining delivery plans in a Business to Consumer (B2C) context. More precisely, we present a refinement of the model given in Carrabs et al.…”

“…In particular, taking into account also the social need and the impact that distribution of goods has on citizens, in the current decade, many studies have been proposed aimed at sustainable urban mobility, especially from a smart city perspective (Carrabs et al. 2017 ; Kauf 2019 ; Szymczyk and Kadłubek 2019 ; Strale 2019 ).…”

“…More precisely, we present a refinement of the model given in Carrabs et al. ( 2017 ), by including valid inequalities and examining additional constraints, depending on the vehicle type and EURO-Class. The minimization of emissions and pollution reduction is the main objective or part of the generalized cost function in many VRPs.…”

An Exact Approach for Selecting Pickup-Delivery Stations in Urban Areas to Reduce Distribution Emission Costs

“…Constraints (4) impose that the distance between each customer and each pds should not exceed the given maximum distance D. Constraints ( 5), ( 6), (10) and (11) ensures that from node w must leave at most one outgoing and ingoing edge, for each customer ∈ C and pds ∈ P. The two different delivery tours of the goods are defined in the following constraints. Indeed, constraints (7) and ( 8) are the classical TSP formulation involving each customer ∈ C served by the warehouse and defining the partitioning between the set Q and Q . Constraints ( 12) and ( 13) are the classical TSP formulation involving each pds ∈ P. More precisely, these constraints guarantee that each node must have only one outgoing edge and only one ingoing edge, that is each node must have a predecessor node and a successor node in the circuit.…”

Simulating impacts of regulatory policies on urban freight: application to the catering setting

“…The new vehicles will entail extra costs that will eventually be paid by the final customers. Moreover, work carried out in [22] shows that an extra cost is already being paid by the citizens in terms of negative externalities (e.g. diseases caused by pollution have social and financial costs).…”