Nowadays, the need to think about sustainable mobility, both goods and people, is widely recognized. For this reason, many recent papers have moved in this direction. In this context, particular attention is now devoted to urban mobility, mainly from a smart city perspective. The present work focuses on sustainable urban freight distribution and proposes a variant of the VRP, which presents some innovative aspects. The goal is to minimize the routes’ cost components, including traveling and external costs due to environmental issues, depending on the chosen vehicles and the different urban streets to cross. In addition, restrictions on the maximum duration of each route to ensure frequent sanitation of vehicles used for deliveries, as required from the beginning of the COVID-19 pandemic, are imposed. The distribution network is modeled by a weighted digraph for which some properties are proved. To face the problem, we present a mixed-integer linear programming model, a math-heuristic associated with it, and a memetic algorithm approach. The results of the reported computational experimentation with random instances specifically tailored for the problem show the efficiency of the proposed methods. Further, test cases based on data of the distribution network of two B2C companies operating in the city of Genoa, Italy, proved the effective application of the proposed methods in the direction of sustainable urban distribution plans.

VRP in urban areas to optimize costs while mitigating environmental impact

Cerrone Carmine;Sciomachen Anna
2022-01-01

Abstract

Nowadays, the need to think about sustainable mobility, both goods and people, is widely recognized. For this reason, many recent papers have moved in this direction. In this context, particular attention is now devoted to urban mobility, mainly from a smart city perspective. The present work focuses on sustainable urban freight distribution and proposes a variant of the VRP, which presents some innovative aspects. The goal is to minimize the routes’ cost components, including traveling and external costs due to environmental issues, depending on the chosen vehicles and the different urban streets to cross. In addition, restrictions on the maximum duration of each route to ensure frequent sanitation of vehicles used for deliveries, as required from the beginning of the COVID-19 pandemic, are imposed. The distribution network is modeled by a weighted digraph for which some properties are proved. To face the problem, we present a mixed-integer linear programming model, a math-heuristic associated with it, and a memetic algorithm approach. The results of the reported computational experimentation with random instances specifically tailored for the problem show the efficiency of the proposed methods. Further, test cases based on data of the distribution network of two B2C companies operating in the city of Genoa, Italy, proved the effective application of the proposed methods in the direction of sustainable urban distribution plans.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1094197
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 4
  • ???jsp.display-item.citation.isi??? 3
social impact