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Optimization Model and Algorithms of Vehicle Scheduling

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (10 October 2024) | Viewed by 8183

Special Issue Editor


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Guest Editor
College of Engineering & Applied Science, University of Wisconsin-Milwaukee, Milwaukee, WI 53211, USA
Interests: vehicle routing; production scheduling; facility layout; semiconductor production scheduling

Special Issue Information

Dear Colleagues,

Today, although information can travel fast at a low cost, the transportation of freight or other physical objects via various types of vehicles largely relies on traditional forms, and, possibly, we will continue to use them until there are further advancements in additive manufacturing or other point-of-use production technologies. While the scale of distribution and transportation has become larger due to the globalization of social and economic systems, people need such advanced information technology services more frequently, such as e-commerce. Additionally, global disasters, such as the COVID-19 pandemic, can restrict people’s mobility while requiring quick access to personal protective equipment (PPE) and other daily necessities. 

The efficient planning of vehicle routing not only improves the efficiency of a system, but also reduces natural resource consumption and protects the environment. Although algorithmic studies play a central role in vehicle routing and scheduling, modern technology provides us with new tools, such as big computation power, artificial intelligence (AI), machine learning (ML), big data, sensor technology, auto navigation, and drones.   

This Special Issue aims to collect advanced research on VRP to provide an update on the state-of-the-art studies being carried out and to provide directions for future research. We invite original research papers on VRP related to these topics: algorithmic modeling, real-time control, AI/ML/big data, energy, the environment, disasters, and new application areas.

Dr. Jaejin Jang
Guest Editor

Manuscript Submission Information

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Keywords

  • supply chain
  • vehicle routing
  • algorithmic study
  • uncertainty
  • AI and sensor application
  • environment
  • disaster
  • new application

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Published Papers (3 papers)

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Research

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18 pages, 2116 KiB  
Article
Multi-Objective Optimization of Pick-Up and Delivery Operations in Bike-Sharing Systems Using a Hybrid Genetic Algorithm
by Heejong Lim, Kwanghun Chung and Sangbok Lee
Appl. Sci. 2024, 14(15), 6703; https://doi.org/10.3390/app14156703 - 1 Aug 2024
Viewed by 684
Abstract
In this study, we present a framework for optimizing pick-up and delivery operations in bike-sharing systems (BSSs), with particular emphasis on inventory rebalancing and vehicle routing to enhance operational efficiency. By employing a hybrid genetic algorithm (HGA), this study integrates sophisticated predictive models [...] Read more.
In this study, we present a framework for optimizing pick-up and delivery operations in bike-sharing systems (BSSs), with particular emphasis on inventory rebalancing and vehicle routing to enhance operational efficiency. By employing a hybrid genetic algorithm (HGA), this study integrates sophisticated predictive models with multi-objective optimization techniques to strike a balance between operational efficiency and demand fulfillment in urban bike-share networks. For probabilistic demand forecasting, the DeepAR model is applied to a large number of bike stations clustered by geological proximity to enable stochastic inventory management. Our proposed HGA approach leverages both the genetic algorithm for generating feasible vehicle routes and mixed-integer programming for bike rebalancing to minimize travel distances while maintaining balanced inventory levels across all clustered stations. Through rigorous empirical evaluations, we demonstrate the effectiveness of our proposed methodology in improving service quality, thus making significant contributions to sustainable urban mobility. This study not only pushes the boundaries of theoretical knowledge in BSS logistics optimization but also offers managerial insights for practical implementation, particularly in densely populated urban settings. Full article
(This article belongs to the Special Issue Optimization Model and Algorithms of Vehicle Scheduling)
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11 pages, 1362 KiB  
Article
Urban Logistics through River: A Two-Echelon Distribution Model
by Angie Ramirez-Villamil, Jairo R. Montoya-Torres and Anicia Jaegler
Appl. Sci. 2023, 13(12), 7259; https://doi.org/10.3390/app13127259 - 18 Jun 2023
Cited by 4 | Viewed by 2225
Abstract
Studies that use rivers in a last-mile delivery context are scarce. This research considers the first multimodal alternative based on a barge for parcel delivery activities. It proposes two sustainable network designs for a two-echelon distribution. The efficiency of scenarios is assessed through [...] Read more.
Studies that use rivers in a last-mile delivery context are scarce. This research considers the first multimodal alternative based on a barge for parcel delivery activities. It proposes two sustainable network designs for a two-echelon distribution. The efficiency of scenarios is assessed through performance indicators. A three-stage decomposition heuristic is used. Allocation of the customers to the closest satellite at the first stage uses a non-supervised machine learning clustering method, 2D-k-means. The last two stages, comprising the two echelons routing, are solved using a heuristic based on the nearest neighbor procedure. The fixed costs decrease by 41% and energy consumption by 92% when applying a river transportation mode and e-cargo bikes in the distribution network’s first and second echelon, respectively. Future research avenues are to render the results more realistic with the consideration of other costs and a larger network. Full article
(This article belongs to the Special Issue Optimization Model and Algorithms of Vehicle Scheduling)
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Review

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27 pages, 2521 KiB  
Review
A Review of Literature on Vehicle Routing Problems of Last-Mile Delivery in Urban Areas
by Reza Jazemi, Ensieh Alidadiani, Kwangseog Ahn and Jaejin Jang
Appl. Sci. 2023, 13(24), 13015; https://doi.org/10.3390/app132413015 - 6 Dec 2023
Cited by 3 | Viewed by 3257
Abstract
Logistics has long been important in an industrial society. Compared with the traditional structure of distribution, which requires freight to be delivered mostly to warehouses or retail stores, customers now often prefer packages to be delivered to their residences, especially after the delivery [...] Read more.
Logistics has long been important in an industrial society. Compared with the traditional structure of distribution, which requires freight to be delivered mostly to warehouses or retail stores, customers now often prefer packages to be delivered to their residences, especially after the delivery challenges during the COVID-19 pandemic. The delivery of parcels to urban residential areas increases the challenge due to the amount of delivery volume, tight delivery schedules, and continuously changing delivery conditions. Last-mile delivery tries to address the challenges, taking advantage of the available automation, sensor and communication technologies, and people’s attitudes toward parcel delivery for the benefit of all stakeholders. Various approaches to last-mile delivery have been proposed and analyzed in the literature. This paper reviews the recent literature on vehicle routing for last-mile delivery. The review identified four major categories: crowdshipping, parcel lockers, delivery by sidekicks, and delivery to optional points. The nature of the problems is discussed in five aspects: fleet capacity, time window, fleet option, dynamism of input, and stochastic parameters. The review identifies the achievements and limitations of the research in the areas and proposes a future research agenda. Full article
(This article belongs to the Special Issue Optimization Model and Algorithms of Vehicle Scheduling)
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