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Algorithms
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Optimization for Vehicle Routing Problems
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Optimization for Vehicle Routing Problems

A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Combinatorial Optimization, Graph, and Network Algorithms".

Deadline for manuscript submissions: closed (15 October 2023) | Viewed by 3829

Special Issue Editor

Dr. Antonio Polimeni

E-Mail Website
Guest Editor
Department of Engineering, University of Messina, 98166 Messina, Italy
Interests: transport system simulation; city logistics; freight transport
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Vehicle Routing Problem is one of the best-known combinatorial optimization problems. In the last decades the research focuses on the proposal for new formulations and the design of new solution procedures. On the other hand, practitioners and logistic operators focus on organizing routes that minimize fleets costs and provide satisfactory services to their customers (citizens, retailers, and industrial users). These two objectives are often at odds but can be met with the use of an optimization approach. Besides, the emerging of new technologies (like electric vehicles and drones), the new trends in urban sustainability, and the increase in e-commerce still make VRP a relevant problem. Then, the VRP (and its variants) are linked with the real-life problems and require the search for new solutions and efficient approaches.

Therefore, the aim of this Special Issue is to collect new works in this field, taking into consideration the challenges deriving from the use of new technologies and the change in the users' habits.

The topics of interest include but are not limited to the following:

  • Heuristic approaches for vehicle routing
  • Exact approaches for vehicle routing
  • Hybrid approaches for vehicle routing
  • Bio-inspired approaches for vehicle routing
  • Vehicle Routing Problem and sustainability
  • Vehicle Routing and green vehicles
  • Vehicle Routing and Intelligent Transportation Systems
  • Vehicle Routing in real time
  • Vehicle Routing with stochastic costs
  • Vehicle Routing in congested road networks
  • Vehicle Routing and dynamic programming
  • Case studies

Dr. Antonio Polimeni
Guest Editor

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. Algorithms 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 1600 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

  • vehicle routing problem
  • traveling salesman problem
  • exact algorithms
  • heuristics metaheuristics
  • bio-inspired algorithms
  • combinatorial optimization
  • multi-depot vehicle routing problem

Published Papers (2 papers)

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Research

19 pages, 2227 KiB  
Article
Dynamic Demand-Responsive Feeder Bus Network Design for a Short Headway Trunk Line
by Amirreza Nickkar and Young-Jae Lee
Algorithms 2023, 16(11), 506; https://doi.org/10.3390/a16110506 - 31 Oct 2023
Viewed by 1324
Abstract
Recent advancements in technology have increased the potential for demand-responsive feeder transit services to enhance mobility in areas with limited public transit access. For long rail headways, feeder bus network algorithms are straightforward, as the maximum feeder service cycle time is determined by [...] Read more.
Recent advancements in technology have increased the potential for demand-responsive feeder transit services to enhance mobility in areas with limited public transit access. For long rail headways, feeder bus network algorithms are straightforward, as the maximum feeder service cycle time is determined by rail headway, and bus–train matching is unnecessary. However, for short rail headways, the algorithm must address both passenger–feeder-bus and feeder-bus–train matching. This study presents a simulated annealing (SA) algorithm for flexible feeder bus routing, accommodating short headway trunk lines and multiple bus relocations for various stations and trains. A 5 min headway rail trunk line example was utilized to test the algorithm. The algorithm effectively managed bus relocations when optimal routes were infeasible at specific stations. Additionally, the algorithm minimized total costs, accounting for vehicle operating expenses and passenger in-vehicle travel time costs, while considering multiple vehicle relocations. Full article
(This article belongs to the Special Issue Optimization for Vehicle Routing Problems)
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16 pages, 1014 KiB  
Article
The Importance of Modeling Path Choice Behavior in the Vehicle Routing Problem
by Antonino Vitetta
Algorithms 2023, 16(1), 47; https://doi.org/10.3390/a16010047 - 10 Jan 2023
Cited by 2 | Viewed by 1503
Abstract
Given two pick-up and delivery points, the best path chosen does not necessarily follow the criteria of minimum travel time or generalized minimum cost evaluated with a deterministic approach. Given a criterion, the perceived cost is not deterministic for many reasons (congestion, incomplete [...] Read more.
Given two pick-up and delivery points, the best path chosen does not necessarily follow the criteria of minimum travel time or generalized minimum cost evaluated with a deterministic approach. Given a criterion, the perceived cost is not deterministic for many reasons (congestion, incomplete information on the state of the system, inexact prediction of the system state, etc.). The same consideration applies to the best-chosen route, assuming that the route is an ordered list of network nodes to visit. The paths and routes perceived and chosen (drivers or companies) could follow different criteria (i.e., minizmum congested travel time for the path and minimum monetary cost for the route). In this context, the paths chosen between two pick-up and delivery points, studied with the path choice problem (PCP), influence the best route, studied with the vehicle routing problem (VRP). This paper reports some considerations on the importance of modelling the path choice behavior in the VRP; the influence of the PCP on the VRP is studied. The considerations are supported by a numerical example in a small network in which the results obtained by adopting the deterministic or probabilistic models for the PCP are compared. To validate the reported thesis, the models are applied in a small test system, and it allows the reader to follow the numerical results step by step. Full article
(This article belongs to the Special Issue Optimization for Vehicle Routing Problems)
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