Advances in Capacitated Vehicle Routing Problem—Models, Methods, Applications and New Challenges: 2nd Edition

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

Deadline for manuscript submissions: closed (20 February 2024) | Viewed by 2496

Special Issue Editors

Department of Electrical Engineering and Computer Science, Kielce University of Technology, Kielce, Poland
Interests: modeling and solving problems with constraints in manufacturing, distribution, logistics, etc.; decision support; optimization; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The capacitated vehicle routing problem (CVRP) is a key to efficient distribution, transportation and supply chain coordination. In broad terms, it deals with the optimal assignment of a set of transportation tasks to a fleet of vehicles and the sequencing of stops for each vehicle. Currently, due to the development of means of transport, the concept of a vehicle is much broader (AVG, UAV, EV, etc.). The CVRP has a large number of real-life applications and comes in many variants, depending on the type of task, the objective, the time frames and the types of constraints that must be met. The CVRP is a computationally hard discrete optimization problem. Outside of transportation, logistics and supply chains, the CVRP has less intuitive but still important applications, e.g., in robotics and manufacturing.

For this Special Issue titled “Advances in Capacitated Vehicle Routing Problem—Models, Methods, Applications and New Challenges”, we invite authors to submit articles that take up the discussion and present solutions in the field of models, methods, applications and new challenges for the CVRP.

Prof. Dr. Paweł Sitek
Dr. Jarosław Wikarek
Guest Editors

Manuscript Submission Information

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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

  • supply chains
  • urban transportation
  • last-mile logistics
  • allocation of resources
  • multi-modal processes
  • AI-driven approach to modeling and solving CVRP
  • UAV fleet routing and scheduling
  • milk-run systems
  • dynamic routing and scheduling
  • fuzzy CVRP
  • production routing

Published Papers (2 papers)

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Research

16 pages, 1240 KiB  
Article
Dynamic Reactive Assignment of Tasks in Real-Time Automated Guided Vehicle Environments with Potential Interruptions
Appl. Sci. 2023, 13(6), 3708; https://doi.org/10.3390/app13063708 - 14 Mar 2023
Cited by 2 | Viewed by 1257
Abstract
An efficient management of production plants has to consider several external and internal factors, such as potential interruptions of the ongoing processes. Automated guided vehicles (AGVs) are becoming a widespread technology that offers many advantages. These AGVs can perform complex tasks in an [...] Read more.
An efficient management of production plants has to consider several external and internal factors, such as potential interruptions of the ongoing processes. Automated guided vehicles (AGVs) are becoming a widespread technology that offers many advantages. These AGVs can perform complex tasks in an autonomous way. However, an inefficient schedule of the tasks assigned to an AGV can suffer from unwanted interruptions and idle times, which in turn will affect the total time required by the AGV to complete its assigned tasks. In order to avoid these issues, this paper proposes a heuristic-based approach that: (i) makes use of a delay matrix to estimate circuit delays for different daily times; (ii) employs these estimates to define an initial itinerary of tasks for an AGV; and (iii) dynamically adjusts the initial agenda as new information on actual delays is obtained by the system. The objective is to minimize the total time required for the AGV to complete all the assigned tasks, taking into account situations that generate unexpected disruptions along the circuits that the AGV follows. In order to test and validate the proposed approach, a series of computational experiments utilizing real-life data are carried out. These experiments allow us to measure the improvement gap with respect to the former policy used by the system managers. Full article
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21 pages, 1068 KiB  
Article
Dual-Sourcing Inventory Routing Problem with Route-Dependent Lead Times in Rolling Horizon Framework
Appl. Sci. 2023, 13(4), 2229; https://doi.org/10.3390/app13042229 - 09 Feb 2023
Viewed by 915
Abstract
Traditional inventory routing problems ignore the time consumption in transportation. In this paper, an inventory routing problem with air–land transportation and route-dependent lead times is studied. The model is based on the rolling horizon framework which can serve as a “here-and-now” approximation for [...] Read more.
Traditional inventory routing problems ignore the time consumption in transportation. In this paper, an inventory routing problem with air–land transportation and route-dependent lead times is studied. The model is based on the rolling horizon framework which can serve as a “here-and-now” approximation for multi-period inventory routing problems. A planning horizon crossing strategy is proposed to consider the effect of the single-period decision on long-term planning. The box uncertainty set is used to depict demands. A tractable closed-form robust solution for optimal replenishment quantity is derived. An adaptive variable neighborhood search algorithm is developed for this problem. A novel shaking phase is proposed, and the performance of shaking operators is evaluated in numerical experiments. Results also validate the effectiveness of the robust solution and the planning horizon crossing strategy. Full article
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