The transportation and logistics sectors are major contributors to Greenhouse Gase(GHG)emissions.Carbon dioxide(CO_(2))from Light-Duty Vehicles(LDVs)is posing serious risks to air quality and public health.Understandi...The transportation and logistics sectors are major contributors to Greenhouse Gase(GHG)emissions.Carbon dioxide(CO_(2))from Light-Duty Vehicles(LDVs)is posing serious risks to air quality and public health.Understanding the extent of LDVs’impact on climate change and human well-being is crucial for informed decisionmaking and effective mitigation strategies.This study investigates the predictability of CO_(2)emissions from LDVs using a comprehensive dataset that includes vehicles from various manufacturers,their CO_(2)emission levels,and key influencing factors.Specifically,sixMachine Learning(ML)algorithms,ranging fromsimple linearmodels to complex non-linear models,were applied under identical conditions to ensure a fair comparison and their performance metrics were calculated.The obtained results showed a significant influence of variables such as engine size on CO_(2)emissions.Although the six algorithms have provided accurate forecasts,the Linear Regression(LR)model was found to be sufficient,achieving a Mean Absolute Percentage Error(MAPE)below 0.90%and a Coefficient of Determination(R2)exceeding 99.7%.These findings may contribute to a deeper understanding of LDVs’role in CO_(2)emissions and offer actionable insights for reducing their environmental impact.In fact,vehicle manufacturers can leverage these insights to target key emission-related factors,while policymakers and stakeholders in logistics and transportation can use the models to estimate the CO_(2)emissions of new vehicles before their market deployment or to project future emissions from current and expected LDV fleets.展开更多
According to the development trend of intelligent logistics in our country, combining database, communication, GIS （Geography lnfolrnation System） technology, the paper study the key core technology of each module m...According to the development trend of intelligent logistics in our country, combining database, communication, GIS （Geography lnfolrnation System） technology, the paper study the key core technology of each module monitoring platform for vehicle monitoring system, and establish logistics transport vehicle monitoring platform that oriented small and medium-sized logistics enterprises, to realize the whole process of real-time monitoring for logistics and transport the vehicle from the warehouse to transportation, promote the informationization of logistics and transport.展开更多
This paper investigated the interaction effects between inventory and transportation strategies in the logistics network. Demand volumes and shipping sizes were simulated as part of a new conceptual model using a disc...This paper investigated the interaction effects between inventory and transportation strategies in the logistics network. Demand volumes and shipping sizes were simulated as part of a new conceptual model using a discrete event simulation by minimizing the total logistics cost in the supply chain. The experiments indicate that the full truckload scenario leads to cost efficiency and the larger demand size results in smaller cost per unit based on economies of scale. Considering the interaction effects, demand size has a greater impact on cost reduction than shipping size. The total logistics cost in the system is dependent on replenishment rate and flow rates from the higher to the lower echelon. High inventory cost is the result of a fast replenishment rate and frequent orders, while shipping cost is dependent on the flow rates in a process and total travelling time or total travelling distance. Shipping size also has an impact on the level of service and the total cost along with effective order variability.展开更多
As the core area of the China-Singapore(Chongqing)Connectivity Initiative(CCI),Chongqing Liangjiang New Area has continuously promoted cooperation with Singapore over the last decade in the key areas of financial serv...As the core area of the China-Singapore(Chongqing)Connectivity Initiative(CCI),Chongqing Liangjiang New Area has continuously promoted cooperation with Singapore over the last decade in the key areas of financial services,aviation,transportation and logistics,and information and communication,which has contributed to the efforts to build a leading inland opening-up and international cooperation zone in Chongqing.So far,the New Area has signed contracts on 90 cooperation projects with Singapore,accounting for 26 percent of the city’s total,which are worth more than US$11.15 billion,43 percent of the city’s total.展开更多
The Vehicle Routing Problem with Time Windows(VRPTW)presents a significant challenge in combinatorial optimization,especially under real-world uncertainties such as variable travel times,service durations,and dynamic ...The Vehicle Routing Problem with Time Windows(VRPTW)presents a significant challenge in combinatorial optimization,especially under real-world uncertainties such as variable travel times,service durations,and dynamic customer demands.These uncertainties make traditional deterministic models inadequate,often leading to suboptimal or infeasible solutions.To address these challenges,this work proposes an adaptive hybrid metaheuristic that integrates Genetic Algorithms(GA)with Local Search(LS),while incorporating stochastic uncertainty modeling through probabilistic travel times.The proposed algorithm dynamically adjusts parameters—such as mutation rate and local search probability—based on real-time search performance.This adaptivity enhances the algorithm’s ability to balance exploration and exploitation during the optimization process.Travel time uncertainties are modeled using Gaussian noise,and solution robustness is evaluated through scenario-based simulations.We test our method on a set of benchmark problems from Solomon’s instance suite,comparing its performance under deterministic and stochastic conditions.Results show that the proposed hybrid approach achieves up to a 9%reduction in expected total travel time and a 40% reduction in time window violations compared to baseline methods,including classical GA and non-adaptive hybrids.Additionally,the algorithm demonstrates strong robustness,with lower solution variance across uncertainty scenarios,and converges faster than competing approaches.These findings highlight the method’s suitability for practical logistics applications such as last-mile delivery and real-time transportation planning,where uncertainty and service-level constraints are critical.The flexibility and effectiveness of the proposed framework make it a promising candidate for deployment in dynamic,uncertainty-aware supply chain environments.展开更多
Human beings and their activities are now connected through Internet of Things(IoT)with the evolution of wireless communication technologies.IoT is becoming popular and its usage is immensely increasing among various ...Human beings and their activities are now connected through Internet of Things(IoT)with the evolution of wireless communication technologies.IoT is becoming popular and its usage is immensely increasing among various sectors.In this research paper,a comprehensive review has been conducted by considering recent and important literature review on IoT applications being operated in three major sectors.The three sectors studied are health,sports and transportation and logistics.Paper explored that with the help of IoT techniques,different miniature sized devices are invented which can record various parameters of human body,wearables devices have been invented which are playing important role in monitoring and recording daily fitness are working on CIoT technology and IoT emergence in the field of transportation and logistics helps in resolving several issues including conveniences,navigation issues,service cost and security issues.All the papers reviewed are journal published from 2010 to 2020.In latter part,this paper also highlighted security,privacy,reliability,consumption of various resources and policies as significant challenges for IoT.展开更多
A systematic approach is proposed to the theme of safety,reliability and global quality of complex networks(material and immaterial)by means of special mathematical tools that allow an adequate geometric characterizat...A systematic approach is proposed to the theme of safety,reliability and global quality of complex networks(material and immaterial)by means of special mathematical tools that allow an adequate geometric characterization and study of the operation,even in the presence of multiple obstacles along the path.To that end,applying the theory of graphs to the problem under study and using a special mathematical model based on stochastic geometry,in this article we consider some regular lattices in which it is possible to schematize the elements of the network,with the fundamental cell with six,eight or 2(n+2)obstacles,calculating the probability of Laplace.In this way it is possible to measure the“degree of impedance”exerted by the anomalies along the network by the obstacles examined.The method can be extended to other regular and/or irregular geometric figures,whose union together constitutes the examined network,allowing to optimize the functioning of the complex system considered.展开更多
In 2014, 32,675 deaths were recorded in vehicle crashes within the United States. Out of these, 51% of the fatalities occurred in rural highways compared to 49% in urban highways. No specific crash data are available ...In 2014, 32,675 deaths were recorded in vehicle crashes within the United States. Out of these, 51% of the fatalities occurred in rural highways compared to 49% in urban highways. No specific crash data are available for the built-up areas along rural highways. Due to high fatalities in rural highways, it is important to identify the factors that cause the vehicle crashes. The main objective of this study is to determine the factors associated with se- verities of crashes that occurred in built-up areas along the rural highways of Nevada. Those factors could aid in making informed decisions while setting up speed zones in these built-up areas. Using descriptive statistics and binary logistic regression model, 337 crashes that occurred in 11 towns along the rural highways from 2002 to 2010 were analyzed. The results showed that more crashes occurred during favorable driving conditions, e.g., 87% crashes on dry roads and 70% crashes in clear weather. The binary logistic regression model showed that crashes occurred from midnight until 4 a.m. were 58.3% likely to be injury crashes rather than property damage only crashes, when other factors were kept at their mean values. Crashes on weekdays were three times more likely to be injury crashes than that occurred on weekends. When other factors were kept at their mean value, crashes involving motorcycles had an 80.2% probability of being injury crashes. Speeding was found to be 17 times more responsible for injury crashes than mechanical defects of the vehicle. As a result of this study, the Nevada Department of Transportation now can take various steps to improve public safety, including steps to reduce speeding and encourage the use of helmets for motorcycle riders.展开更多
基金Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia,project number MoE-IF-UJ-R2-22-20772-1.
文摘The transportation and logistics sectors are major contributors to Greenhouse Gase(GHG)emissions.Carbon dioxide(CO_(2))from Light-Duty Vehicles(LDVs)is posing serious risks to air quality and public health.Understanding the extent of LDVs’impact on climate change and human well-being is crucial for informed decisionmaking and effective mitigation strategies.This study investigates the predictability of CO_(2)emissions from LDVs using a comprehensive dataset that includes vehicles from various manufacturers,their CO_(2)emission levels,and key influencing factors.Specifically,sixMachine Learning(ML)algorithms,ranging fromsimple linearmodels to complex non-linear models,were applied under identical conditions to ensure a fair comparison and their performance metrics were calculated.The obtained results showed a significant influence of variables such as engine size on CO_(2)emissions.Although the six algorithms have provided accurate forecasts,the Linear Regression(LR)model was found to be sufficient,achieving a Mean Absolute Percentage Error(MAPE)below 0.90%and a Coefficient of Determination(R2)exceeding 99.7%.These findings may contribute to a deeper understanding of LDVs’role in CO_(2)emissions and offer actionable insights for reducing their environmental impact.In fact,vehicle manufacturers can leverage these insights to target key emission-related factors,while policymakers and stakeholders in logistics and transportation can use the models to estimate the CO_(2)emissions of new vehicles before their market deployment or to project future emissions from current and expected LDV fleets.
文摘According to the development trend of intelligent logistics in our country, combining database, communication, GIS （Geography lnfolrnation System） technology, the paper study the key core technology of each module monitoring platform for vehicle monitoring system, and establish logistics transport vehicle monitoring platform that oriented small and medium-sized logistics enterprises, to realize the whole process of real-time monitoring for logistics and transport the vehicle from the warehouse to transportation, promote the informationization of logistics and transport.
文摘This paper investigated the interaction effects between inventory and transportation strategies in the logistics network. Demand volumes and shipping sizes were simulated as part of a new conceptual model using a discrete event simulation by minimizing the total logistics cost in the supply chain. The experiments indicate that the full truckload scenario leads to cost efficiency and the larger demand size results in smaller cost per unit based on economies of scale. Considering the interaction effects, demand size has a greater impact on cost reduction than shipping size. The total logistics cost in the system is dependent on replenishment rate and flow rates from the higher to the lower echelon. High inventory cost is the result of a fast replenishment rate and frequent orders, while shipping cost is dependent on the flow rates in a process and total travelling time or total travelling distance. Shipping size also has an impact on the level of service and the total cost along with effective order variability.
文摘As the core area of the China-Singapore(Chongqing)Connectivity Initiative(CCI),Chongqing Liangjiang New Area has continuously promoted cooperation with Singapore over the last decade in the key areas of financial services,aviation,transportation and logistics,and information and communication,which has contributed to the efforts to build a leading inland opening-up and international cooperation zone in Chongqing.So far,the New Area has signed contracts on 90 cooperation projects with Singapore,accounting for 26 percent of the city’s total,which are worth more than US$11.15 billion,43 percent of the city’s total.
文摘The Vehicle Routing Problem with Time Windows(VRPTW)presents a significant challenge in combinatorial optimization,especially under real-world uncertainties such as variable travel times,service durations,and dynamic customer demands.These uncertainties make traditional deterministic models inadequate,often leading to suboptimal or infeasible solutions.To address these challenges,this work proposes an adaptive hybrid metaheuristic that integrates Genetic Algorithms(GA)with Local Search(LS),while incorporating stochastic uncertainty modeling through probabilistic travel times.The proposed algorithm dynamically adjusts parameters—such as mutation rate and local search probability—based on real-time search performance.This adaptivity enhances the algorithm’s ability to balance exploration and exploitation during the optimization process.Travel time uncertainties are modeled using Gaussian noise,and solution robustness is evaluated through scenario-based simulations.We test our method on a set of benchmark problems from Solomon’s instance suite,comparing its performance under deterministic and stochastic conditions.Results show that the proposed hybrid approach achieves up to a 9%reduction in expected total travel time and a 40% reduction in time window violations compared to baseline methods,including classical GA and non-adaptive hybrids.Additionally,the algorithm demonstrates strong robustness,with lower solution variance across uncertainty scenarios,and converges faster than competing approaches.These findings highlight the method’s suitability for practical logistics applications such as last-mile delivery and real-time transportation planning,where uncertainty and service-level constraints are critical.The flexibility and effectiveness of the proposed framework make it a promising candidate for deployment in dynamic,uncertainty-aware supply chain environments.
文摘Human beings and their activities are now connected through Internet of Things(IoT)with the evolution of wireless communication technologies.IoT is becoming popular and its usage is immensely increasing among various sectors.In this research paper,a comprehensive review has been conducted by considering recent and important literature review on IoT applications being operated in three major sectors.The three sectors studied are health,sports and transportation and logistics.Paper explored that with the help of IoT techniques,different miniature sized devices are invented which can record various parameters of human body,wearables devices have been invented which are playing important role in monitoring and recording daily fitness are working on CIoT technology and IoT emergence in the field of transportation and logistics helps in resolving several issues including conveniences,navigation issues,service cost and security issues.All the papers reviewed are journal published from 2010 to 2020.In latter part,this paper also highlighted security,privacy,reliability,consumption of various resources and policies as significant challenges for IoT.
文摘A systematic approach is proposed to the theme of safety,reliability and global quality of complex networks(material and immaterial)by means of special mathematical tools that allow an adequate geometric characterization and study of the operation,even in the presence of multiple obstacles along the path.To that end,applying the theory of graphs to the problem under study and using a special mathematical model based on stochastic geometry,in this article we consider some regular lattices in which it is possible to schematize the elements of the network,with the fundamental cell with six,eight or 2(n+2)obstacles,calculating the probability of Laplace.In this way it is possible to measure the“degree of impedance”exerted by the anomalies along the network by the obstacles examined.The method can be extended to other regular and/or irregular geometric figures,whose union together constitutes the examined network,allowing to optimize the functioning of the complex system considered.
基金Nevada Department of Transportation(NDOT)for funding the studyprovided under grant#P255-11-803 by NDOT
文摘In 2014, 32,675 deaths were recorded in vehicle crashes within the United States. Out of these, 51% of the fatalities occurred in rural highways compared to 49% in urban highways. No specific crash data are available for the built-up areas along rural highways. Due to high fatalities in rural highways, it is important to identify the factors that cause the vehicle crashes. The main objective of this study is to determine the factors associated with se- verities of crashes that occurred in built-up areas along the rural highways of Nevada. Those factors could aid in making informed decisions while setting up speed zones in these built-up areas. Using descriptive statistics and binary logistic regression model, 337 crashes that occurred in 11 towns along the rural highways from 2002 to 2010 were analyzed. The results showed that more crashes occurred during favorable driving conditions, e.g., 87% crashes on dry roads and 70% crashes in clear weather. The binary logistic regression model showed that crashes occurred from midnight until 4 a.m. were 58.3% likely to be injury crashes rather than property damage only crashes, when other factors were kept at their mean values. Crashes on weekdays were three times more likely to be injury crashes than that occurred on weekends. When other factors were kept at their mean value, crashes involving motorcycles had an 80.2% probability of being injury crashes. Speeding was found to be 17 times more responsible for injury crashes than mechanical defects of the vehicle. As a result of this study, the Nevada Department of Transportation now can take various steps to improve public safety, including steps to reduce speeding and encourage the use of helmets for motorcycle riders.
