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Advanced Methods and Applications in Routing and Distributions Problems

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Transportation and Future Mobility".

Deadline for manuscript submissions: 20 August 2025 | Viewed by 1193

Special Issue Editors


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Centre for Mechanical Engineering, Materials and Processes, ARISE, University of Coimbra, 3004-531 Coimbra, Portugal
Interests: operations research; computer science; industrial engineering; logistics
Special Issues, Collections and Topics in MDPI journals

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1. Mechanical Engineering Department, Polytechnic University of Leiria, 2411-901 Leiria, Portugal
2. ALGORITMI Centre, University of Minho, 4704-553 Braga, Portugal
Interests: discrete-event simulation; lean healthcare; lean operations management; production planning and control
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Industrial Engineering and Management, Faculty of Engineering, Lusófona University and EIGeS, Campo Grande, 1749-024 Lisbon, Portugal
Interests: operations management; decision support; optimization; production planning and scheduling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Vehicle Routing Problem (VRP) and its variants play a vital role in the logistics and supply chain management sectors. This Special Issue aims to bring together cutting-edge research and innovative methodologies addressing complex issues related to these problems, emphasizing both theoretical advancements and practical applications. The scope includes, but is not limited to, novel mathematical modelling formulations; innovative, advanced optimization strategies; and real-world implementations of the VRP or other integrated optimization problems embedding the VRP.

Key topics explored in this issue encompass heuristic and metaheuristic approaches, exact algorithms, hybridization methods, and machine learning approaches. Furthermore, the issue delves into advanced distribution challenges, including uncertainty, robustness, real-time routing problems, and integrating new energy sources or sustainable practices.

Encouraging contributions from both academia and industry, this Special Issue aims to advance the state of the art in routing and distribution. We invite original research papers addressing new methodologies and real cases in collaboration with industry, providing new insights and significant contributions to the field.

Dr. Telmo Miguel Pires Pinto
Dr. Bruno Gonçalves
Dr. Miguel Vieira
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2400 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

  • routing
  • distribution
  • advanced logistics
  • multi-echelon networks
  • computational logistics

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Published Papers (1 paper)

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Research

21 pages, 2370 KiB  
Article
Time-Dependent Vehicle Routing Problem with Drones Under Vehicle Restricted Zones and No-Fly Zones
by Shuo Wei, Houming Fan, Xiaoxue Ren and Xiaolong Diao
Appl. Sci. 2025, 15(4), 2207; https://doi.org/10.3390/app15042207 - 19 Feb 2025
Cited by 1 | Viewed by 702
Abstract
This paper addresses the time-dependent vehicle routing problem with drones in vehicle-restricted zones and no-fly zones (TDVRPD-VRZ-NFZ). The optimization model considers the impacts of vehicle-restricted zones, no-fly zones, and time-dependent road networks on delivery paths. The objective is to minimize the total cost, [...] Read more.
This paper addresses the time-dependent vehicle routing problem with drones in vehicle-restricted zones and no-fly zones (TDVRPD-VRZ-NFZ). The optimization model considers the impacts of vehicle-restricted zones, no-fly zones, and time-dependent road networks on delivery paths. The objective is to minimize the total cost, including vehicle dispatch costs, energy consumption costs for vehicles and drones, and time-window penalty costs. The model is verified for correctness using Gurobi. In response to the problem’s characteristics, a hybrid genetic algorithm and variable neighborhood search with a learning mechanism (HGAVNS-LM) is proposed to solve the problem. The algorithm starts by generating the initial population using a combination of logistic mapping and reverse learning. It then improves the genetic operators and variable neighborhood search operators to optimize the initial population. To improve the algorithm’s performance, an individual elite archive is used for knowledge learning, and a self-learning mechanism is established to dynamically adjust the algorithm’s key parameters. The solution obtained by HGAVNS-LM shows a deviation of −0.2% to −0.3% compared to Gurobi, but it saves 99.68% in solving time. Compared to the genetic neighborhood search algorithm and the hybrid genetic algorithm, the improvement rates are 5.1% and 13.0%, respectively. Through the analysis of multiple sets of test cases, it is concluded that time-varying road networks, vehicle-restricted zones and no-fly zones, and different detour rules all affect delivery costs and delivery plans. The research results provide a more scientific theoretical basis for logistics companies to customize delivery solutions. Full article
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