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Smart Cities
Special Issues
City Logistics and Smart Cities: Models, Approaches and Planning
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City Logistics and Smart Cities: Models, Approaches and Planning

A special issue of Smart Cities (ISSN 2624-6511).

Deadline for manuscript submissions: closed (30 September 2025) | Viewed by 16360

Special Issue Editors

Dr. Antonio Polimeni

E-Mail Website
Guest Editor
Department of Engineering, University of Messina, 98158 Messina, Italy
Interests: city logistics; passenger transportation; vehicle routing problem; road network design
Special Issues, Collections and Topics in MDPI journals
Dr. Orlando M. Belcore

E-Mail Website
Guest Editor
Department of Engineering, University of Messina, 98158 Messina, Italy
Interests: city logistics; demand modelling; discrete event simulation; port performance
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

City logistics aims to optimize the logistics and the transport activities in urban areas, considering their interaction with other traffic components with the support of new technologies. These activities must consider the sustainability and livability of the urban context (e.g., environmental impacts, safety). The issues connected with the recent increase in online purchases, also influenced by COVID-19, posed new problems to solve and new challenges to face. Therefore, it emerges that city logistics require the development of integrated and dynamic solutions, for example, those based on information and communication technologies (ICTs) and intelligent transport systems (ITSs). To support these solutions, simulation models, design approaches, and planning must be implemented. The aim is to identify, simulate, and optimize all the activities that characterize city logistics and its impacts on the city.

Therefore, the purpose of this Special Issue is to gather new research in this field, considering the challenges resulting from the use of new technologies. The topics of interest include but are not limited to the following:

  • Discrete models in city logistics;
  • Planning urban freight distribution;
  • City logistics management and control;
  • Travel cost and learning processes;
  • Vehicle routes optimization in urban areas;
  • Forecasting end consumer choices;
  • Forecasting urban freight flows;
  • ICTs and ITSs for city logistics;
  • Analysis of the impacts of city logistics;
  • Green vehicles;
  • Shopping trips;
  • New services for city logistics (crowd shipping, parcel lockers, etc.)

Dr. Antonio Polimeni
Dr. Orlando M. Belcore
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Smart Cities is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • city logistics
  • urban freight distribution
  • green urban logistics
  • e-commerce
  • green vehicles
  • city logistics management
  • light freight vehicles
  • freight vehicle route optimization
  • city logistics planning

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

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Research

33 pages, 7428 KB  
Article
Constrained Metropolitan Service Placement: Integrating Bayesian Optimization with Spatial Heuristics
by Tatiana Churiakova, Ivan Platonov, Mark Bezmaslov, Vadim Bikbulatov, Ovanes Petrosian, Vasilii Starikov and Sergey A. Mityagin
Smart Cities 2026, 9(1), 6; https://doi.org/10.3390/smartcities9010006 - 26 Dec 2025
Viewed by 765
Abstract
Metropolitan service-placement optimization is computationally challenging under strict evaluation budgets and regulatory constraints. Existing approaches either neglect capacity constraints, producing infeasible solutions, or employ population-based metaheuristics requiring hundreds of evaluations—beyond typical municipal planning resources. We introduce a two-stage optimization framework combining Bayesian optimization [...] Read more.
Metropolitan service-placement optimization is computationally challenging under strict evaluation budgets and regulatory constraints. Existing approaches either neglect capacity constraints, producing infeasible solutions, or employ population-based metaheuristics requiring hundreds of evaluations—beyond typical municipal planning resources. We introduce a two-stage optimization framework combining Bayesian optimization with domain-informed heuristics to address this constrained, mixed discrete–continuous problem. Stage 1 optimizes continuous service area allocations via the Tree-structured Parzen Estimator with empirical gradient prioritization, reducing effective dimensionality from 81 services to 10–15 per iteration. Stage 2 converts allocations into discrete unit placements via efficiency-ranked bin packing, ensuring regulatory compliance. Evaluation across 35 benchmarks on Saint Petersburg, Russia (117–3060 decision variables), demonstrates that our method achieves 99.4% of the global optimum under a 50-evaluation budget, outperforming BIPOP-CMA-ES (98.4%), PURE-TPE (97.1%), and NSGA-II (96.5%). Optimized configurations improve equity (Gini coefficient of 0.318 → 0.241) while maintaining computational feasibility (2.7 h for 109-block districts). Open-source implementation supports reproducibility and facilitates adoption in metropolitan planning practice. Full article
(This article belongs to the Special Issue City Logistics and Smart Cities: Models, Approaches and Planning)
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20 pages, 4264 KB  
Article
Electric Vehicle Charging Logistics in Spain: An In-Depth Analysis
by Juan Antonio Martínez-Lao, Antonio García-Chica, Silvia Sánchez-Salinas, Eduardo José Viciana-Gámez and Alejandro Cama-Pinto
Smart Cities 2025, 8(2), 50; https://doi.org/10.3390/smartcities8020050 - 13 Mar 2025
Viewed by 4921
Abstract
Spain’s National Integrated Energy and Climate Plan (PNIEC) addresses the policies and measures needed to contribute to the European target of a 23% reduction in greenhouse gas emissions by 2030 compared to 1990 levels. To this end, the decarbonization of the transport sector [...] Read more.
Spain’s National Integrated Energy and Climate Plan (PNIEC) addresses the policies and measures needed to contribute to the European target of a 23% reduction in greenhouse gas emissions by 2030 compared to 1990 levels. To this end, the decarbonization of the transport sector is very important in order to increase electric mobility. Electric mobility depends on the conditions of the electrical infrastructure. This research focuses on the electrical distribution network in terms of its current capacity for recharging electric vehicles, which are estimated to account for 20.7% of vehicles, which is about 4 million vehicles. This, therefore, illustrates the need to legislate to improve the electrical infrastructure for recharging electric vehicles, with the aim of deploying electric vehicles on a larger scale and, ultimately, allowing society to benefit from the advantages of this technology. Full article
(This article belongs to the Special Issue City Logistics and Smart Cities: Models, Approaches and Planning)
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20 pages, 7549 KB  
Article
Development of a Delivery Time-Period Selection Model for Urban Freight Using GPS Data
by Ryota Kodera, Takanori Sakai and Tetsuro Hyodo
Smart Cities 2025, 8(1), 31; https://doi.org/10.3390/smartcities8010031 - 13 Feb 2025
Cited by 1 | Viewed by 3437
Abstract
Developing policy instruments related to urban freight, such as congestion pricing, urban consolidation schemes, and off-hours delivery, requires an understanding of the distribution of shipment delivery times. Furthermore, agent-based urban freight simulators use relevant information (shipment delivery time distribution or vehicle tour start [...] Read more.
Developing policy instruments related to urban freight, such as congestion pricing, urban consolidation schemes, and off-hours delivery, requires an understanding of the distribution of shipment delivery times. Furthermore, agent-based urban freight simulators use relevant information (shipment delivery time distribution or vehicle tour start time distribution) as input to simulate tour generation. However, studies focusing on shipment delivery time-period selection modeling are very limited. In this study, we propose a method using GPS trajectory data from the Tokyo Metropolitan Area to estimate a shipment delivery time-period selection model based on pseudo-shipment records inferred from GPS data. The results indicate that shipment distance, size, and destination attributes can explain the delivery times of goods. Moreover, we demonstrate the practicality of the model by comparing the simulation result with the observed data for three areas with distinct characteristics, concluding that the model could be applied to urban freight simulation models for accurately reproducing spatial heterogeneity in shipment delivery time periods. This study contributes to promoting smart city development and management by proposing a method to use big data to better understand deliveries and support the development of relevant advanced city logistics solutions. Full article
(This article belongs to the Special Issue City Logistics and Smart Cities: Models, Approaches and Planning)
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21 pages, 3077 KB  
Article
Drone-Assisted Last-Mile Delivery Under Windy Conditions: Zero Pollution Solutions
by Özlem Gürel and Seyda Serdarasan
Smart Cities 2024, 7(6), 3437-3457; https://doi.org/10.3390/smartcities7060134 - 10 Nov 2024
Cited by 7 | Viewed by 6015
Abstract
As cities expand and the global push for zero pollution intensifies, sustainable last-mile delivery (LMD) systems are essential to minimizing environmental and health impacts. This study addresses the need for more sustainable LMD by examining the integration of wind conditions into drone-assisted deliveries, [...] Read more.
As cities expand and the global push for zero pollution intensifies, sustainable last-mile delivery (LMD) systems are essential to minimizing environmental and health impacts. This study addresses the need for more sustainable LMD by examining the integration of wind conditions into drone-assisted deliveries, focusing on their effects on air and noise pollution in urban areas. We extend the flying sidekick traveling salesman problem (FSTSP) by incorporating meteorological factors, specifically wind, to assess drone delivery efficiency in varying conditions. Our results show that while drones significantly reduce greenhouse gas emissions compared to traditional delivery vehicles, their contribution to noise pollution remains a concern. This research highlights the environmental advantages of using drones, particularly in reducing CO2 emissions, while also emphasizing the need for further investigation into mitigating their noise impact. By evaluating the trade-offs between air and noise pollution, this study provides insights into developing more sustainable, health-conscious delivery models that contribute to smart city initiatives. The findings inform policy, urban planning, and logistics strategies aimed at achieving zero pollution goals and improving urban livability. Full article
(This article belongs to the Special Issue City Logistics and Smart Cities: Models, Approaches and Planning)
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