The amount of perishable products transported via the existing intermodal freight networks has significantly increased over the last years. Perishable products tend to decay due to a wide range of external factors. Su...The amount of perishable products transported via the existing intermodal freight networks has significantly increased over the last years. Perishable products tend to decay due to a wide range of external factors. Supply chain operations mismanagement causes waste of substantial volumes of perishable products every year. The heretofore proposed mathematical models optimize certain supply chain processes and reduce decay of perishable products, but primarily deal with local production, inventory, distribution, and retailing of perishable products. However, significant quantities of perishable products are delivered from different continents, which shall increase the total transportation time and decay potential of perishable products as compared to local deliveries. This paper proposes a novel optimization model to design the intermodal freight network for both local and long-haul deliveries of perishable products. The objective of the model aims to minimize the total cost associated with transportation and decay of perishable products. A set of piecewise approximations are applied to linearize the non-linear decay function for each perishable product type. CPLEX is used to solve the problem. Comprehensive numerical experiments are conducted using the intermodal freight network for import of the seafood perishable products to the United States to draw important managerial insights. Results demonstrate that increasing product decay cost may significantly change the design of intermodal freight network for transport of perishable products, cause modal shifts and affect the total transportation time and associated costs.展开更多
This study examined the spatio-temporal trajectories of the international freight forwarding service(IFFS) in the Yangtze River Delta(YRD) and explored the driving mechanisms of the service. Based on a bipartite netwo...This study examined the spatio-temporal trajectories of the international freight forwarding service(IFFS) in the Yangtze River Delta(YRD) and explored the driving mechanisms of the service. Based on a bipartite network projection from an IFFS firm-city data source, we mapped three IFFS networks in the YRD in 2005, 2010, and 2015. A range of statistical indicators were used to explore changes in the spatial patterns of the three networks. The underlying influence of marketization, globalization, decentralization, and integration was then explored. It was found that the connections between Shanghai and other nodal cities formed the backbones of these networks. The effects of a city's administrative level and provincial administrative borders were generally obvious. We found several specific spatial patterns associated with IFFS. For example, the four non-administrative centers of Ningbo, Suzhou, Lianyungang, and Nantong were the most connected cities and played the role of gateway cities. Furthermore, remarkable regional equalities were found regarding a city's IFFS network provision, with notable examples in the weakly connected areas of northern Jiangsu and southwestern Zhejiang. Finally, an analysis of the driving mechanisms demonstrated that IFFS network changes were highly sensitive to the influences of marketization and globalization, while regional integration played a lesser role in driving changes in IFFS networks.展开更多
This paper presents a general framework that can be used to estimate direct and cross elasticities for freight transport using a network model. This methodology combines operational research (network assignments in a ...This paper presents a general framework that can be used to estimate direct and cross elasticities for freight transport using a network model. This methodology combines operational research (network assignments in a geographical information system) with more classical econometrics (multinomial logit choice models). The application of the method to a real-world case is illustrated by a simple model that relies on the generalized cost of transport as the only explanatory variable in the utility function. The methodological framework allows, however, for the implementation of more complex functions. Beside the generalized cost functions for road, rail and inland waterways transport, the network model needs origin-destination matrixes and digitized networks. They are imported from ETIS Plus, a European transport policy information system. A set of direct and cross elasticities is presented. The estimated values are obtained using two methods: the first computes standard elasticities, while the second estimates arc elasticities. Figures are presented for Europe and for a large region around the Benelux countries, where more competition exists between the three modes of interest.展开更多
为解决网络货运平台价格预测不准确导致的成交率下降问题,提出基于Shingling检索的表格先验数据拟合网络(tabular prior-data fitted network,TabPFN)的局部上下文学习(local context learning with TabPFN based on shingling retrieva...为解决网络货运平台价格预测不准确导致的成交率下降问题,提出基于Shingling检索的表格先验数据拟合网络(tabular prior-data fitted network,TabPFN)的局部上下文学习(local context learning with TabPFN based on shingling retrieval,ShinglingPFN)模型。首先,该模型运用w-Shingling检索算法,从历史订单数据中匹配出与预测订单最相似的订单,构建局部关联的上下文数据。然后,加载并初始化预训练的TabPFN模型实例,将筛选出的订单数据输入模型,让TabPFN基于这些上下文信息学习货运特征与运费的关联模式。最后,输出该货运样本的运费预测结果。结果表明,ShinglingPFN模型相比随机森林(random forest,RF)模型减少了30.98%的平均绝对误差(mean absolute error,MAE)。通过全局敏感性分析,进一步增强了模型的可解释性。ShinglingPFN模型可为平台优化定价策略提供决策支撑。展开更多
Strategic transportation network models are often used as support tools in the framework of decisions to be taken at the policy level, such as the Trans-European Network projects. These models are mostly setup using a...Strategic transportation network models are often used as support tools in the framework of decisions to be taken at the policy level, such as the Trans-European Network projects. These models are mostly setup using aggregated or limited data. If their calibration is regularly mentioned in the literature, their validation is barely discussed. In this paper, several modal choice model specifications that make only use of explanatory variables available at the network level are described and applied to a large scale case. A validation exercise is performed at three levels of aggregation. The paper is designed from a strategic transport planning perspective, and does not present new modal choice formulations or assignment procedures. Its main added value is the focus on calibration and validation considerations. Despite the limited explanatory information used, the global performance of the best models can be considered as satisfactory. However, the quality of the models varies from mode to mode, the use of railway transport being the most difficult to predict without more specific input.展开更多
Baltic Exchange Dirty Tanker Index (BDTI) is an important assessment index in world dirty tanker shipping industry. Actors in the industry sector can gain numerous benefits from accurate forecasting of the BDTI. Howev...Baltic Exchange Dirty Tanker Index (BDTI) is an important assessment index in world dirty tanker shipping industry. Actors in the industry sector can gain numerous benefits from accurate forecasting of the BDTI. However, limitations exist in traditional stochastic and econometric explanation modeling techniques used in freight rate forecasting. At the same time research in shipping index forecasting e.g. BDTI applying artificial intelligent techniques is scarce. This analyses the possibilities to forecast the BDTI by applying Wavelet Neural Networks (WNN). Firstly, the characteristics of traditional and artificial intelligent forecasting techniques are discussed and rationales for choosing WNN are explained. Secondly, the components and features of BDTI will be explicated. After that, the authors delve the determinants and influencing factors behind fluctuations of the BDTI in order to set inputs for WNN forecasting model. The paper examines non-linearity and non-stationary features of the BDTI and elaborates WNN model building procedures. Finally, the comparison of forecasting performance between WNN and ARIMA time series models show that WNN has better forecasting accuracy than traditionally used modeling techniques.展开更多
文摘The amount of perishable products transported via the existing intermodal freight networks has significantly increased over the last years. Perishable products tend to decay due to a wide range of external factors. Supply chain operations mismanagement causes waste of substantial volumes of perishable products every year. The heretofore proposed mathematical models optimize certain supply chain processes and reduce decay of perishable products, but primarily deal with local production, inventory, distribution, and retailing of perishable products. However, significant quantities of perishable products are delivered from different continents, which shall increase the total transportation time and decay potential of perishable products as compared to local deliveries. This paper proposes a novel optimization model to design the intermodal freight network for both local and long-haul deliveries of perishable products. The objective of the model aims to minimize the total cost associated with transportation and decay of perishable products. A set of piecewise approximations are applied to linearize the non-linear decay function for each perishable product type. CPLEX is used to solve the problem. Comprehensive numerical experiments are conducted using the intermodal freight network for import of the seafood perishable products to the United States to draw important managerial insights. Results demonstrate that increasing product decay cost may significantly change the design of intermodal freight network for transport of perishable products, cause modal shifts and affect the total transportation time and associated costs.
基金National Natural Science Foundation of China(No.41671132,41771139)Natural Science Foundation of Jiangsu Province(No.BK20171516)
文摘This study examined the spatio-temporal trajectories of the international freight forwarding service(IFFS) in the Yangtze River Delta(YRD) and explored the driving mechanisms of the service. Based on a bipartite network projection from an IFFS firm-city data source, we mapped three IFFS networks in the YRD in 2005, 2010, and 2015. A range of statistical indicators were used to explore changes in the spatial patterns of the three networks. The underlying influence of marketization, globalization, decentralization, and integration was then explored. It was found that the connections between Shanghai and other nodal cities formed the backbones of these networks. The effects of a city's administrative level and provincial administrative borders were generally obvious. We found several specific spatial patterns associated with IFFS. For example, the four non-administrative centers of Ningbo, Suzhou, Lianyungang, and Nantong were the most connected cities and played the role of gateway cities. Furthermore, remarkable regional equalities were found regarding a city's IFFS network provision, with notable examples in the weakly connected areas of northern Jiangsu and southwestern Zhejiang. Finally, an analysis of the driving mechanisms demonstrated that IFFS network changes were highly sensitive to the influences of marketization and globalization, while regional integration played a lesser role in driving changes in IFFS networks.
文摘This paper presents a general framework that can be used to estimate direct and cross elasticities for freight transport using a network model. This methodology combines operational research (network assignments in a geographical information system) with more classical econometrics (multinomial logit choice models). The application of the method to a real-world case is illustrated by a simple model that relies on the generalized cost of transport as the only explanatory variable in the utility function. The methodological framework allows, however, for the implementation of more complex functions. Beside the generalized cost functions for road, rail and inland waterways transport, the network model needs origin-destination matrixes and digitized networks. They are imported from ETIS Plus, a European transport policy information system. A set of direct and cross elasticities is presented. The estimated values are obtained using two methods: the first computes standard elasticities, while the second estimates arc elasticities. Figures are presented for Europe and for a large region around the Benelux countries, where more competition exists between the three modes of interest.
文摘为解决网络货运平台价格预测不准确导致的成交率下降问题,提出基于Shingling检索的表格先验数据拟合网络(tabular prior-data fitted network,TabPFN)的局部上下文学习(local context learning with TabPFN based on shingling retrieval,ShinglingPFN)模型。首先,该模型运用w-Shingling检索算法,从历史订单数据中匹配出与预测订单最相似的订单,构建局部关联的上下文数据。然后,加载并初始化预训练的TabPFN模型实例,将筛选出的订单数据输入模型,让TabPFN基于这些上下文信息学习货运特征与运费的关联模式。最后,输出该货运样本的运费预测结果。结果表明,ShinglingPFN模型相比随机森林(random forest,RF)模型减少了30.98%的平均绝对误差(mean absolute error,MAE)。通过全局敏感性分析,进一步增强了模型的可解释性。ShinglingPFN模型可为平台优化定价策略提供决策支撑。
文摘Strategic transportation network models are often used as support tools in the framework of decisions to be taken at the policy level, such as the Trans-European Network projects. These models are mostly setup using aggregated or limited data. If their calibration is regularly mentioned in the literature, their validation is barely discussed. In this paper, several modal choice model specifications that make only use of explanatory variables available at the network level are described and applied to a large scale case. A validation exercise is performed at three levels of aggregation. The paper is designed from a strategic transport planning perspective, and does not present new modal choice formulations or assignment procedures. Its main added value is the focus on calibration and validation considerations. Despite the limited explanatory information used, the global performance of the best models can be considered as satisfactory. However, the quality of the models varies from mode to mode, the use of railway transport being the most difficult to predict without more specific input.
文摘Baltic Exchange Dirty Tanker Index (BDTI) is an important assessment index in world dirty tanker shipping industry. Actors in the industry sector can gain numerous benefits from accurate forecasting of the BDTI. However, limitations exist in traditional stochastic and econometric explanation modeling techniques used in freight rate forecasting. At the same time research in shipping index forecasting e.g. BDTI applying artificial intelligent techniques is scarce. This analyses the possibilities to forecast the BDTI by applying Wavelet Neural Networks (WNN). Firstly, the characteristics of traditional and artificial intelligent forecasting techniques are discussed and rationales for choosing WNN are explained. Secondly, the components and features of BDTI will be explicated. After that, the authors delve the determinants and influencing factors behind fluctuations of the BDTI in order to set inputs for WNN forecasting model. The paper examines non-linearity and non-stationary features of the BDTI and elaborates WNN model building procedures. Finally, the comparison of forecasting performance between WNN and ARIMA time series models show that WNN has better forecasting accuracy than traditionally used modeling techniques.
