Vehicle Routing Optimization for Vaccine Distribution Considering Reducing Energy Consumption

Yu, Runfeng; Liu, Yun; Chen, Chen; Tang, Yuanjie; Fan, Hong-Yi; Qu, Yi

doi:10.3390/su15021252

Cited by 4 publications

(5 citation statements)

References 50 publications

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“…The green cost equals to the fuel cost plus the carbon tax, which further depend on the amount of fuel consumption. According to the literature [36][37][38][39][40], the fuel consumption of vehicles is…”

Section: Objective Function Analysis Of Model 1 Fixed Costsmentioning

confidence: 99%

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Optimization of “vehicle-UAV” joint distribution routing for cold chain logistics considering risk of epidemic spreading and green cost

Liu,

Guo

et al. 2024

PLoS ONE

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To address the epidemic, such as COVID-19, the government may implement the home quarantine policy for the infected residents. The logistics company is required to control the risk of epidemic spreading while delivering goods to residents. In this case, the logistics company often uses vehicles and unmanned aerial vehicles (UAVs) for delivery. This paper studies the distribution issue of cold chain logistics by integrating UAV logistics with epidemic risk management innovatively. At first, a "vehicle-UAV" joint distribution mode including vehicles, small UAVs and large UAVs, is proposed. The green cost for vehicles and UAVs is calculated, respectively. The formula for infection risk due to large numbers of residents gathering at distribution centers to pick up goods is then derived. Furthermore, based on the control of infection risk, an optimization model is developed to minimize the total logistics cost. A modified ant colony algorithm is designed to solve the model. The numerical results show that the maximum acceptable risk and the crowd management level of distribution centers both have significant effects on the distribution network, logistics cost and number of new infections. Our study provides a new management method and technical idea for ensuring the needs of residents during the epidemic.

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Section: Objective Function Analysis Of Model 1 Fixed Costsmentioning

confidence: 99%

“…Eq (36) implies that a large UVA team can fly to a housing estate only if the team has been assigned to service the estate. Eq (39) sets that any large UAV team cannot stop at any housing estate finally. Eqs (40)(41) are computational formulas of D w 0 ; D w s , the goods weight of a team of large UAVs just arriving at a housing estate.…”

Section: Subject Tomentioning

confidence: 99%

Optimization of “vehicle-UAV” joint distribution routing for cold chain logistics considering risk of epidemic spreading and green cost

Liu,

Guo

et al. 2024

PLoS ONE

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“…• condition of traffic flow additivity (23), according to which traffic flows along various O-D pairs and routes add together on common transport links:…”

Section: Case Studymentioning

confidence: 99%

“…Simple models are easy to create and analyse but may provide incomplete information about the studied system and consequently lead to incorrect conclusions. On the other hand, too complex models are very time-consuming (also cost-consuming), and excessive volumes of information can alter the reliable analysis of processes and phenomena [22,23].…”

Section: Introductionmentioning

confidence: 99%

Nash Equilibrium and Stackelberg Approach for Traffic Flow Optimization in Road Transportation Networks—A Case Study of Warsaw

et al. 2023

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The article discusses the issue of modelling traffic flows and the transport network. Faced with an increase in the number of vehicles in road networks, the problem of congestion and the need to optimise traffic and adapt the transport infrastructure to changing demand are growing, especially in large cities. With this in mind, the authors of this publication developed a model of the road network in the north-eastern part of the Warsaw agglomeration based on the proposed algorithm. Two methods were used to optimise the distribution of traffic flows: the Nash equilibrium and the Stackelberg approach. The Nash equilibrium assumes the aim of achieving equal average times on all roads for each origin–destination (O-D) pair. This describes the state pursued by a decentralised system guided by the individual benefits of the traffic users. On the contrary, the Stackelberg approach aims to achieve optimal travel times for the entire system. The study was carried out for three scenarios that differed in the assumed traffic demand on the road network. The basic scenario assumed the average hourly traffic demand during the morning peak hour based on traffic measurements. On the other hand, the two alternative scenarios were developed as a 10% variation in traffic volumes from the baseline scenario. On the basis of the results, it was concluded that an increase in traffic volumes for all O-D pairs could result in a decrease in traffic volumes on some links of the road network. This means that the transport network is a complex system and any change in parameters can cause significant and difficult to predict changes. Therefore, the proposed approach is useful in terms of traffic forecasting for road networks under conditions of changing traffic flow volumes. Additionally, the total travel time for the entire system differed for each scenario by a percentage difference of 0.67–1.07% between the optimal solution according to the Nash equilibrium and the Stackelberg approach.

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“…Note that the Solomon insertion I1 heuristic only generates feasible solutions to this model without considering the quality or the objective value. The process of finding better solutions will be conducted by the GA operator [84]. The review above explicitly demonstrates that within the domain of meta-heuristic methodologies employed for addressing VRP models, GA has exhibited noteworthy superiority over alternative techniques.…”

mentioning

confidence: 99%

Logistics Optimization Using Hybrid Genetic Algorithm (HGA): A Solution to the Vehicle Routing Problem With Time Windows (VRPTW)

Maroof,

Ayvaz,

Naeem

2024

IEEE Access

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The Vehicle Routing Problem with Time Windows (VRPTW) is paramount in elevating operational efficiency, driving cost reductions, and enhancing customer satisfaction. It is a renowned challenge with diverse real-world applications, where the core objective is determining the most efficient routes for a fleet of vehicles. This research introduces a cutting-edge Hybrid Genetic Algorithm-Solomon Insertion Heuristic (HGA-SIH) solution, reinforced by the powerful Solomon Insertion constructive heuristic to solve the VRPTW as an NP-hard problem. The performance of the proposed HGA-SIH is validated against Solomon's VRPTW benchmark instances. The results showcase the outstanding performance of HGA, achieving Best-Known Solutions (BKS) for 11 instances and enhancing BKS solutions in one instance. Experimental findings validate that HGA-SIH consistently delivers results on par with or surpasses those obtained by several cutting-edge algorithms when evaluated based on various solution quality metrics. HGA-SIH consistently excels in efficiently managing the number of vehicles while minimizing travel distances, resulting in slight deviations from BKS that remain within practical limits. The research highlights the adaptability and efficacy of HGA-SIH in addressing a wide range of VRPTW scenarios, thereby making substantial contributions to logistics and supply chain optimization.

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Vehicle Routing Optimization for Vaccine Distribution Considering Reducing Energy Consumption

Cited by 4 publications

References 50 publications

Optimization of “vehicle-UAV” joint distribution routing for cold chain logistics considering risk of epidemic spreading and green cost

Optimization of “vehicle-UAV” joint distribution routing for cold chain logistics considering risk of epidemic spreading and green cost

Nash Equilibrium and Stackelberg Approach for Traffic Flow Optimization in Road Transportation Networks—A Case Study of Warsaw

Logistics Optimization Using Hybrid Genetic Algorithm (HGA): A Solution to the Vehicle Routing Problem With Time Windows (VRPTW)

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