The long-haul full-load vehicle routing and truck driver scheduling problem with intermediate stops: An economic impact evaluation of Brazilian policy

Mayerle, Sérgio Fernando; Chiroli, Daiane Maria De Genaro; Figueiredo, João Neiva de; Rodrigues, Hidelbrando Ferreira

doi:10.1016/j.tra.2020.07.021

Cited by 7 publications

(5 citation statements)

References 23 publications

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“…Equation (10) indicates that the number of customer nodes of a single route in each distribution area does not exceed the total number of customers in the distribution area. Equa-tion (11) indicates that all customer nodes can be served by vehicles. Equation (12) shows that the carrying capacity of the vehicle departing from the distribution center is the sum of the distribution demand of the vehicle in the distribution route.…”

Section: Model Hypothesismentioning

confidence: 99%

“…Liu et al developed a deep inverse reinforcement learning (IRL) algorithm and employed Dijkstra's algorithm instead of value iteration, to determine the current policy and compute the gradient of IRL [10]. In order to optimize the route selection of long distance vehicles in Brazil, Mayerle et al pro-posed a joint solution for the routing and scheduling problem with time window constraints, determining simultaneously a routing plan [11].…”

Section: Introductionmentioning

confidence: 99%

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Optimization Model and Algorithm of Cigarette Distribution Route Based on Cluster Analysis

Xiao

Wang

et al. 2022

Wireless Communications and Mobile Computing

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Cigarette distribution is an important part of the tobacco logistics supply chain, and it will affect the distribution cost, efficiency, and service quality. In this paper，we choose a two-stage optimization method to analyze the cigarette distribution route across the Administrative Region in China. First, we use a K-means clustering algorithm to generate an initial center. Then, we optimize the clustering region with the vehicle load and workload as constraints. Finally, we establish the cigarette distribution route optimization model by taking the lowest distribution cost as the objective function. In the model calculation, we not only select the adaptive genetic algorithm as the solution algorithm but also use the scanning algorithm to generate the initial population ,design adaptive crossover and mutation probability, and also design inverse operator to correct the error, and we wish to improve the solution performance of the algorithm by this way.In addition, taking the cigarette distribution of Chongqing Tobacco Logistics as an example, this paper analyzes the number of vehicles, average loading rate, and total distribution distance and distribution cost, and finds that the cross-regional joint distribution route is better than independent distribution. And we also find that using clustering analysis and the genetic algorithm could reduce the amount of computation and solve the problem effectively.

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Section: Model Hypothesismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimization Model and Algorithm of Cigarette Distribution Route Based on Cluster Analysis

Xiao

Wang

et al. 2022

Wireless Communications and Mobile Computing

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“…Tob-Ogu et al (2018) andYasmim et al (2020) highlighted the relevance of investigating the influence of technology adoption in emerging countries. Furthermore, freight transportation operations are essential in the Brazilian context (Mayerle et al, 2020), as this is Brazil's most popular mode of goods transportation (de Souza et al, 2022). Thus, studies on the role of technology in Brazilian road cargo transportation are necessary.…”

Section: Data Visibility In Road Transportationmentioning

confidence: 99%

Illuminating the road ahead: unlocking the potential of ICTs for enhanced data visibility in road transportation

Callefi,

Ganga,

Godinho Filho

et al. 2023

IMDS

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PurposeRoad freight transportation companies need to take advantage of information and communication technologies to develop capabilities. This study proposes a framework to guide road freight transportation companies to achieve data visibility in their operations by developing such capabilities. By proposing this framework, this research contributes to literature and practice, highlighting the capabilities and the respective supporting technologies for improved data visibility in road freight transportation.Design/methodology/approachA mixed-method approach is used to develop the framework, considering three methodological steps. In phase 1, the capabilities are identified in the literature and validated by experts. In phase 2, an empirical assessment of cause–effect relationships between capabilities is performed using a multiple case study and DEMATEL. Lastly, in phase 3, an analysis of the cause model and significant associations is conducted to enable the development of the framework. In addition, the proposed framework was validated by the experts interviewed.FindingsThe results provide a framework that explains the link between the technology-enabled data visibility capabilities in road freight transportation operations. In addition, a pathway was established that road freight transportation companies could follow to achieve data visibility in their operations by developing such capabilities.Originality/valueThis work develops the first framework that provides a path for data visibility in road freight transportation operations from adopting certain technologies. The insights are compelling for researchers and practitioners to optimize the decision-making process for adopting technologies and developing capabilities related to data visibility.

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“…Results of the comparison are interesting and may be helpful to other researchers and practitioners saving time with searching the differences between previous social legislation and the new current legislation and help to better understand the adopted changes of the Regulation (EC) No 561/2006. We hope that this paper will help transport companies in scheduling full-load trips and in business practice to prevent unpleasant experiences resulting from possible compliance with social regulations and also to improve the awareness of drivers in the performance of their work [11].…”

Section: Introductionmentioning

confidence: 99%

Regulation (EC) No 561/2006 - review of the adopted changes on 15 July 2020

Beňuš

Demirci²

2021

The Archives of Automotive Engineering – Archiwum Motoryzacji

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The social legislation is a current and political issue in the field of road freight transport. Working conditions for drivers in the EU (including Switzerland, Norway, Liechtenstein, and Iceland) are governed by Regulation (EC) No 561/2006. Regulation (EC) No 561/2006 - known as the Driving Time Regulation - lays down rules on driving times, breaks and rest periods for drivers of lorries and buses to improve working conditions and road safety. A number of new amendments to this regulation were adopted on 15 July 2020. The aim of this paper is to present the most important changes adopted compared to the previous version of the Regulation. The paper deals with the adopted changes in the following areas: weekly rest periods, secure parking areas, vehicles which are transported by ferry or train and exceeding driving time which may jeopardize road safety. The main purpose of this paper is to summarize and inform researchers, practitioners and all interested parties about the adopted changes in the Regulation, as well as the transport companies responsible for planning and scheduling the working time of drivers and also for preventing unpleasant experiences resulting from possible compliance with the conditions of the Regulation. The adopted changes in Regulation are also illustrated in the figures and table to better understand the differences.

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The long-haul full-load vehicle routing and truck driver scheduling problem with intermediate stops: An economic impact evaluation of Brazilian policy

Cited by 7 publications

References 23 publications

Optimization Model and Algorithm of Cigarette Distribution Route Based on Cluster Analysis

Optimization Model and Algorithm of Cigarette Distribution Route Based on Cluster Analysis

Illuminating the road ahead: unlocking the potential of ICTs for enhanced data visibility in road transportation

Regulation (EC) No 561/2006 - review of the adopted changes on 15 July 2020

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