A Crowdsourcing Approach for Sustainable Last Mile Delivery

Adriana Giret, Carlos Carrascosa, Vicente Julian, Miguel Rebollo and Vicente Botti
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Adriana Giret: Departamento de Sistemas Informáticos y Computación, Universitat Politècnica de València, Camino de Vera s/n. 46022 Valencia, Spain
Carlos Carrascosa: Departamento de Sistemas Informáticos y Computación, Universitat Politècnica de València, Camino de Vera s/n. 46022 Valencia, Spain
Vicente Julian: Departamento de Sistemas Informáticos y Computación, Universitat Politècnica de València, Camino de Vera s/n. 46022 Valencia, Spain
Miguel Rebollo: Departamento de Sistemas Informáticos y Computación, Universitat Politècnica de València, Camino de Vera s/n. 46022 Valencia, Spain
Vicente Botti: Departamento de Sistemas Informáticos y Computación, Universitat Politècnica de València, Camino de Vera s/n. 46022 Valencia, Spain

Sustainability, 2018, vol. 10, issue 12, 1-17

Abstract: Sustainable transportation is one of the major concerns in cities. This concern involves all type of movements motivated by different goals (mobility of citizens, transportation of goods and parcels, etc.). The main goal of this work is to provide an intelligent approach for Sustainable Last Mile Delivery, by reducing (or even deleting) the need of dedicated logistic moves (by cars, and/or trucks). The method attempts to reduce the number of movements originated by the parcels delivery by taking advantage of the citizens’ movements. In this way our proposal follows a crowdsourcing approach, in which the citizens that moves in the city, because of their own needs, become temporal deliverers. The technology behind our approach relays on Multi-agent System techniques and complex network-based algorithms for optimizing sustainable delivery routes. These artificial intelligent approaches help to reduce the complexity of the scenario providing an efficient way to integrate the citizens’ routes that can be executed using the different transportation means and networks available in the city (public system, private transportation, eco-vehicles sharing systems, etc.). A complex network-based algorithm is used for computing and proposing an optimized Sustainable Last Mile Delivery route to the crowd. Moreover, the executed tests show the feasibility of the proposed solution, together with a high reduction of the CO 2 emission coming from the delivery trucks that, in the case studies, are no longer needed for delivery.

Keywords: multi agent techniques; last mile delivery; complex network-based analysis; sustainable delivery (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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