Purpose–This paper aims to provide a comprehensive analysis of the strategic adjustments in China’s transportation structure,with a particular focus on the pivotal role of railway freight and its integration into th...Purpose–This paper aims to provide a comprehensive analysis of the strategic adjustments in China’s transportation structure,with a particular focus on the pivotal role of railway freight and its integration into the modern logistics system.It seeks to address the need for a more nuanced understanding of the“road to rail”policy,emphasizing the importance of intermodal collaboration and service of fragmented market demands.Design/methodology/approach–The study employs a transport economics perspective to evaluate the achievements and shortcomings of China’s transportation structure optimization.It bases its assessment of the current state of railway freight logistics,multi-modal transportation and the broader implications for the transportation service market on data analysis.The methodology includes a review of existing policies,an examination of industry practices and a comparative analysis with global trends in railway logistics.Findings–The research underscores the importance of focusing on the development of non-bulk materials,noting the insufficiency in the development of China’s rail multi-modal transportation and highlighting the instructive value of successful cases in open-top container road-rail intermodal transportation.The study posits that the railway sector must enhance cooperation with other market entities,aligning with the lead enterprises in the logistics chain that are characterized by speed,high value and strong coordination capabilities,in order to better serve the transportation market.This approach moves away from a reliance on the railway’s own capabilities alone.Originality/value–This paper offers original insights into the transformation of railway freight in China,contributing to the body of knowledge on transportation economics and logistics.It provides valuable recommendations for policymakers and industry practitioners,emphasizing the strategic importance of railway logistics in the context of China’s economic development and intense competition in the supply chain.The value of the article lies in its comprehensive understanding of the complexities involved in the adjustment of transportation structures,providing direction for the market-oriented reform of China’s railway freight sector.展开更多
Rural vitalization is a major strategy for reform and development of agriculture and rural areas in China,the key task of which is improving rural living environment.Imperfect rural solid waste(RSW)collection and tran...Rural vitalization is a major strategy for reform and development of agriculture and rural areas in China,the key task of which is improving rural living environment.Imperfect rural solid waste(RSW)collection and transportation system exacerbates the pollution of RSW to rural living environment,while it has not been established and improved in the cold region of Northern China due to climate and economy.Through the analysis of the current situation of RSW source separation,collection,transportation and disposal in China,an RSW collection and transportation system suitable for the northern cold region was developed.Considering the low winter temperature in the northern cold region,different requirements for RSW collection,transportation and terminal disposal,scattered source points and single terminal disposal nodes in rural areas,the study focused on determining the number and location of transfer stations,established a model for transfer stations selection and RSW collection and transportation routes optimization for RSW collection and transportation system,and proposed the elite retention particle swarm optimization–genetic algorithm(ERPSO–GA).The rural area of Baiquan County was taken as a representative case,the collection and transportation scheme of which was given,and the feasibility of the scheme was clarified by simulation experiment.展开更多
We propose a self-organized optimization mechanism to improve the transport capacity of complex gradient networks. We find that, regardless of network topology, the congestion pressure can be strongly reduced by the s...We propose a self-organized optimization mechanism to improve the transport capacity of complex gradient networks. We find that, regardless of network topology, the congestion pressure can be strongly reduced by the self-organized optimization mechanism. Furthermore, the random scale-free topology is more efficient to reduce congestion compared with the random Poisson topology under the optimization mechanism. The reason is that the optimization mechanism introduces the correlations between the gradient field and the local topology of the substrate network. Due to the correlations, the cutoff degree of the gradient network is strongly reduced and the number of the nodes exerting their maximal transport capacity consumedly increases. Our work presents evidence supporting the idea that scale-free networks can efficiently improve their transport capacity by self- organized mechanism under gradient-driven transport mode.展开更多
This paper concerns the weak solutions of some Monge-Amp^re type equa- tions in the optimal transportation theory. The relationship between the Aleksandrov solutions and the viscosity solutions of the Monge-Ampere typ...This paper concerns the weak solutions of some Monge-Amp^re type equa- tions in the optimal transportation theory. The relationship between the Aleksandrov solutions and the viscosity solutions of the Monge-Ampere type equations is discussed. A uniform estimate for solution of the Dirichlet problem with homogeneous boundary value is obtained.展开更多
A theoretical study was conducted on finding optimal paths in transportation networks where link travel times were stochastic and time-dependent(STD). The methodology of relative robust optimization was applied as mea...A theoretical study was conducted on finding optimal paths in transportation networks where link travel times were stochastic and time-dependent(STD). The methodology of relative robust optimization was applied as measures for comparing time-varying, random path travel times for a priori optimization. In accordance with the situation in real world, a stochastic consistent condition was provided for the STD networks and under this condition, a mathematical proof was given that the STD robust optimal path problem can be simplified into a minimum problem in specific time-dependent networks. A label setting algorithm was designed and tested to find travelers' robust optimal path in a sampled STD network with computation complexity of O(n2+n·m). The validity of the robust approach and the designed algorithm were confirmed in the computational tests. Compared with conventional probability approach, the proposed approach is simple and efficient, and also has a good application prospect in navigation system.展开更多
The traditional manner to design public transportation system is to sequentially design the transit network and public bicycle network. A new public transportation system design problem that simultaneously considers b...The traditional manner to design public transportation system is to sequentially design the transit network and public bicycle network. A new public transportation system design problem that simultaneously considers both bus network design and public bicycle network design is proposed. The chemical reaction optimization(CRO) is designed to solve the problem. A shortcoming of CRO is that, when the two-molecule collisions take place, the molecules are randomly picked from the container.Hence, we improve CRO by employing different mating strategies. The computational results confirm the benefits of the mating strategies. Numerical experiments are conducted on the Sioux-Falls network. A comparison with the traditional sequential modeling framework indicates that the proposed approach has a better performance and is more robust. The practical applicability of the approach is proved by employing a real size network.展开更多
When encountering the distribution shift between the source(training) and target(test) domains, domain adaptation attempts to adjust the classifiers to be capable of dealing with different domains. Previous domain ada...When encountering the distribution shift between the source(training) and target(test) domains, domain adaptation attempts to adjust the classifiers to be capable of dealing with different domains. Previous domain adaptation research has achieved a lot of success both in theory and practice under the assumption that all the examples in the source domain are welllabeled and of high quality. However, the methods consistently lose robustness in noisy settings where data from the source domain have corrupted labels or features which is common in reality. Therefore, robust domain adaptation has been introduced to deal with such problems. In this paper, we attempt to solve two interrelated problems with robust domain adaptation:distribution shift across domains and sample noises of the source domain. To disentangle these challenges, an optimal transport approach with low-rank constraints is applied to guide the domain adaptation model training process to avoid noisy information influence. For the domain shift problem, the optimal transport mechanism can learn the joint data representations between the source and target domains using a measurement of discrepancy and preserve the discriminative information. The rank constraint on the transport matrix can help recover the corrupted subspace structures and eliminate the noise to some extent when dealing with corrupted source data. The solution to this relaxed and regularized optimal transport framework is a convex optimization problem that can be solved using the Augmented Lagrange Multiplier method, whose convergence can be mathematically proved. The effectiveness of the proposed method is evaluated through extensive experiments on both synthetic and real-world datasets.展开更多
足球比赛场景中球员居多、足球目标偏小且移动速度快,足球检测识别难度很大。为了解决这一问题,提出一种基于改进的YOLOv5的足球检测方法,增加使用了OTA(Optimal Transport Assignment)损失函数来优化模型提高对足球目标的识别精度,最后...足球比赛场景中球员居多、足球目标偏小且移动速度快,足球检测识别难度很大。为了解决这一问题,提出一种基于改进的YOLOv5的足球检测方法,增加使用了OTA(Optimal Transport Assignment)损失函数来优化模型提高对足球目标的识别精度,最后在Roboflow的足球数据集上进行训练,对足球比赛场景下的足球进行目标检测实现足球识别。根据实验可以得出结论:改进后的YOLOv5算法的足球识别不仅提高了足球的识别性能与精度,而且有效地提高了检测速度,具有更好的识别性能。展开更多
We propose a novel framework for learning a low-dimensional representation of data based on nonlinear dynamical systems,which we call the dynamical dimension reduction(DDR).In the DDR model,each point is evolved via a...We propose a novel framework for learning a low-dimensional representation of data based on nonlinear dynamical systems,which we call the dynamical dimension reduction(DDR).In the DDR model,each point is evolved via a nonlinear flow towards a lower-dimensional subspace;the projection onto the subspace gives the low-dimensional embedding.Training the model involves identifying the nonlinear flow and the subspace.Following the equation discovery method,we represent the vector field that defines the flow using a linear combination of dictionary elements,where each element is a pre-specified linear/nonlinear candidate function.A regularization term for the average total kinetic energy is also introduced and motivated by the optimal transport theory.We prove that the resulting optimization problem is well-posed and establish several properties of the DDR method.We also show how the DDR method can be trained using a gradient-based optimization method,where the gradients are computed using the adjoint method from the optimal control theory.The DDR method is implemented and compared on synthetic and example data sets to other dimension reduction methods,including the PCA,t-SNE,and Umap.展开更多
This work introduces an optimal transportation(OT)view of generative adversarial networks(GANs).Natural datasets have intrinsic patterns,which can be summarized as the manifold distribution principle:the distribution ...This work introduces an optimal transportation(OT)view of generative adversarial networks(GANs).Natural datasets have intrinsic patterns,which can be summarized as the manifold distribution principle:the distribution of a class of data is close to a low-dimensional manifold.GANs mainly accomplish two tasks:manifold learning and probability distribution transformation.The latter can be carried out using the classical OT method.From the OT perspective,the generator computes the OT map,while the discriminator computes the Wasserstein distance between the generated data distribution and the real data distribution;both can be reduced to a convex geometric optimization process.Furthermore,OT theory discovers the intrinsic collaborative-instead of competitive-relation between the generator and the discriminator,and the fundamental reason for mode collapse.We also propose a novel generative model,which uses an autoencoder(AE)for manifold learning and OT map for probability distribution transformation.This AE–OT model improves the theoretical rigor and transparency,as well as the computational stability and efficiency;in particular,it eliminates the mode collapse.The experimental results validate our hypothesis,and demonstrate the advantages of our proposed model.展开更多
In this work,we develop an invertible transport map,called KRnet,for density estimation by coupling the Knothe–Rosenblatt(KR)rearrangement and the flow-based generative model,which generalizes the real-valued non-vol...In this work,we develop an invertible transport map,called KRnet,for density estimation by coupling the Knothe–Rosenblatt(KR)rearrangement and the flow-based generative model,which generalizes the real-valued non-volume preserving(real NVP)model(arX-iv:1605.08803v3).The triangular structure of the KR rearrangement breaks the symmetry of the real NVP in terms of the exchange of information between dimensions,which not only accelerates the training process but also improves the accuracy significantly.We have also introduced several new layers into the generative model to improve both robustness and effectiveness,including a reformulated affine coupling layer,a rotation layer and a component-wise nonlinear invertible layer.The KRnet can be used for both density estimation and sample generation especially when the dimensionality is relatively high.Numerical experiments have been presented to demonstrate the performance of KRnet.展开更多
Despite recent turbulences in global economy, the growth of global trade volumes is expected to continue in the future, leading to increased demands on the performance of logistics networks. The political framework fo...Despite recent turbulences in global economy, the growth of global trade volumes is expected to continue in the future, leading to increased demands on the performance of logistics networks. The political framework for EU （European Union） Transport Policy Development is presented in the EU White Paper on Transport 2011 in order to build a competitive European transport system. One significant aspect is the promotion of multimodal transport in order to decrease terrestrial transport services （road and rail） and to increase services in the maritime transport sector, especially considering the relief of road and railway infrastructure. Looking at the present situation, SSS （Short Sea Shipping） is already used in many different transport fields all around the world. However, there still exists a great potential which currently is not used or not sufficiently exploited for many different reasons. In order to identify the potential use of SSS in multimodal transport, different scenarios in the Baltic Sea Region and the adjoining hinterland have been developed pointing out alternative solutions for routing. These options are analyzed in detail and evaluated from different perspectives （i.e. transport and handling costs, time consumption and transport-related emissions）. Afterwards, advantages and disadvantages of each alternative will be examined by taking into account economic and ecological aspects in making decision.展开更多
Low pressure chemical vapor deposition(LPCVD) is one of the most important processes during semiconductor manufacturing.However,the spatial distribution of internal temperature and extremely few samples makes it hard ...Low pressure chemical vapor deposition(LPCVD) is one of the most important processes during semiconductor manufacturing.However,the spatial distribution of internal temperature and extremely few samples makes it hard to build a good-quality model of this batch process.Besides,due to the properties of this process,the reliability of the model must be taken into consideration when optimizing the MVs.In this work,an optimal design strategy based on the self-learning Gaussian process model(GPM) is proposed to control this kind of spatial batch process.The GPM is utilized as the internal model to predict the thicknesses of thin films on all spatial-distributed wafers using the limited data.Unlike the conventional model based design,the uncertainties of predictions provided by GPM are taken into consideration to guide the optimal design of manipulated variables so that the designing can be more prudent Besides,the GPM is also actively enhanced using as little data as possible based on the predictive uncertainties.The effectiveness of the proposed strategy is successfully demonstrated in an LPCVD process.展开更多
In this exposition paper we present the optimal transport problem of Monge-Ampère-Kantorovitch(MAK in short)and its approximative entropical regularization.Contrary to the MAK optimal transport problem,the soluti...In this exposition paper we present the optimal transport problem of Monge-Ampère-Kantorovitch(MAK in short)and its approximative entropical regularization.Contrary to the MAK optimal transport problem,the solution of the entropical optimal transport problem is always unique,and is characterized by the Schrödinger system.The relationship between the Schrödinger system,the associated Bernstein process and the optimal transport was developed by Léonard[32,33](and by Mikami[39]earlier via an h-process).We present Sinkhorn’s algorithm for solving the Schrödinger system and the recent results on its convergence rate.We study the gradient descent algorithm based on the dual optimal question and prove its exponential convergence,whose rate might be independent of the regularization constant.This exposition is motivated by recent applications of optimal transport to different domains such as machine learning,image processing,econometrics,astrophysics etc..展开更多
Despite of fluctuations in world trade as a result of economic cycles,the evolution of the political processes remains the trend of sustained growth of trade flows.This ends up in a rise in both the demand for logisti...Despite of fluctuations in world trade as a result of economic cycles,the evolution of the political processes remains the trend of sustained growth of trade flows.This ends up in a rise in both the demand for logistics services and the requirements for them.In this sense,the critically important is the strategic development of the transport systems as a support for the improvement of competitive logistics.An important aspect is the promotion of multimodal transport,which in search of the best transport solutions will reduce the use of relatively expensive and environmentally unfriendly road transportation.This will be at the expense of the efficient combination of different modes in which the concept of short sea shipping(SSS)occupies a central place.Although this concept is widely applied in many places in the Black Sea,it still has significant potential.It was prompted by stagnation in economic relations as a result of political and economic crises in the region since the late twentieth and early twenty-first century.To evaluate the potential of the concept in the development of transport is done research on intermodal logistics network in the logistics corridor Central Asia-Central Europe.To optimize intermodal transport links a comparative analysis of the various transport alternatives on the route Tehran-Budapest is done.On this basis it is made optimization assessment on three main criteria cost,delivery time and environmental protection and basic recommendations on strategic planning development of the Bulgarian transport infrastructure are given.An essential aspect is the encouragement of multimodal transportation,which in looking for the best transport solutions can cut back the utilization of comparatively costly and environmentally harmful road transportation.This would be at the expense of the adequate combination of different modes of transportation in which the concept of SSS has a fundamental area.Despite this concept is widely applied in various regions,in the Black Sea it still has an important future due to stagnation in economic relations as a result of political confrontations and economic crises within the region since the late twentieth and early twenty-first century.To assess the capability of the concept in the development of transport is done research on intermodal logistics network in the logistics corridor Central Asia-Central Europe.To improve intermodal transport links a comparative analysis of the various transport options on the routes Astana-Budapest and Tehran-Budapest are made.On this basis it is proposed an optimization assessment on three main criteria cost,delivery time and environmental protection,and fundamental suggestions on strategic development of the Bulgarian transport infrastructure are proposed.展开更多
Purpose–Under the dual pressure of resources and environment,many countries have focused on the role of railways in promoting low-carbon development of integrated transportation and of even the whole society.This pap...Purpose–Under the dual pressure of resources and environment,many countries have focused on the role of railways in promoting low-carbon development of integrated transportation and of even the whole society.This paper aims to provide a comprehensive study on methods to improve railway energy efficiency in other national railways and achievements made by China’s railways in the past practice,and then to propose ways in which in the future China’s railways could rationally select the path of improving energy efficiency regarding the needs of the nation’s ever-shifting development and carry out the re-engineering for mechanism innovation in energy conservation and emission reduction process.Design/methodology/approach–This paper first studies other national railways that have tried to promote the improvement of railway energy efficiency by the ways of technology,management and structural reconstruction to reduce energy consumption and carbon emissions.Among them,the effect of structural energy conservation and emission reduction has become more prominent.It has become the main energy conservation and emission reduction measure adopted by foreign railway sectors.The practice of energy conservation and emission reduction of railways in various countries has tended to shift from a technical level to a structural one.Findings–Key aspects in improving energy efficiency include re-optimization of energy structure,reinnovation of energy-saving technologies and optimization of transportation organization.Path selection includes continuing to promote electrified railway construction,increasing the use of new and renewable energy sources,and promoting the reform of railway transportation organizations.Originality/value–This paper provides further challenges and research directions in the proposed area and has referential value for the methodologies,approaches for practice in a Chinese context.To achieve the expected goals,relevant supporting policies and measures need to be formulated,including actively guiding integrated transportation toward railway-oriented development,promoting innovation in energy-saving and emission reduction mechanisms and strengthening policy incentives,focusing on improving the energy efficiency of railways through market behavior.At the same time,it is necessary to pay attention to new phenomena in the railway industry for track and analysis.展开更多
The long-tailed data distribution poses an enormous challenge for training neural networks in classification.A classification network can be decoupled into a feature extractor and a classifier.This paper takes a semi-...The long-tailed data distribution poses an enormous challenge for training neural networks in classification.A classification network can be decoupled into a feature extractor and a classifier.This paper takes a semi-discrete optimal transport(OT)perspective to analyze the long-tailed classification problem,where the feature space is viewed as a continuous source domain,and the classifier weights are viewed as a discrete target domain.The classifier is indeed to find a cell decomposition of the feature space with each cell corresponding to one class.An imbalanced training set causes the more frequent classes to have larger volume cells,which means that the classifier's decision boundary is biased towards less frequent classes,resulting in reduced classification performance in the inference phase.Therefore,we propose a novel OTdynamic softmax loss,which dynamically adjusts the decision boundary in the training phase to avoid overfitting in the tail classes.In addition,our method incorporates the supervised contrastive loss so that the feature space can satisfy the uniform distribution condition.Extensive and comprehensive experiments demonstrate that our method achieves state-ofthe-art performance on multiple long-tailed recognition benchmarks,including CIFAR-LT,ImageNet-LT,iNaturalist 2018,and Places-LT.展开更多
This study proposes a flexible timetable optimization method based on hybrid vehicle size model to tackle the bus demand fluctuations in transit operation. Three different models for hybrid vehicle, large vehicle and ...This study proposes a flexible timetable optimization method based on hybrid vehicle size model to tackle the bus demand fluctuations in transit operation. Three different models for hybrid vehicle, large vehicle and small vehicle are built in this study, respectively. With the operation data of Shanghai Transit Route 55 at peak and off-peak hours, a heuristic algorithm was proposed to solve the problem. The results indicate that the hybrid vehicle size model excels the other two modes both in the total time and total cost. The study verifies the rationality of the strategy of hybrid vehicle size model and highlights the importance of the adaptive vehicle size in dealing with the bus demand fluctuation. The main innovation of the study is that unlike traditional timetables, the arrangement of the scheduling interval and the corresponding bus type or size are both involved in the timetable of hybrid vehicle size bus mode, which will be more effective to solve the problem of passenger demand fluctuation. Findings from this research would provide a new perspective to improve the level of regular bus service.展开更多
This paper addresses the transportation network design problem （NDP） wherein the dis- tance limit and en-route recharge of electric vehicles are taken into account. Specifically, in this work, the network design pro...This paper addresses the transportation network design problem （NDP） wherein the dis- tance limit and en-route recharge of electric vehicles are taken into account. Specifically, in this work, the network design problem aims to select the optimal planning policy from a set of infrastructure design scenarios considering both road expansions and charging station allocations under a specified construction budget. The user-equilibrium mixed-vehicular traffic assignment problem with en-route recharge （MVTAP-ER） is formulated into a novel convex optimization model and extended to a newly developed bi-level program of the aggregated NDP integrating recharge facility allocation （NDP-RFA）. In the algorithmic framework, a convex optimization technique and a tailored CA are adopted for, respectively, solving the subproblem MVTAP-ER and the primal problem NDP-RFA. Systematic ex- periments are conducted to test the efficacy of the proposed approaches. The results highlight the impacts of distance limits and budget levels on the project selection and evaluation, and the benefits of considering both road improvement policy and recharge service provision as compared to accounting for the latter only. The results also report that the two design objectives, to respectively minimize the total system travel time and vehicle miles travelled, are conflicting for certain scenarios.展开更多
Optimal transportation plays a fundamental role in many fi elds in engineering and medicine,including surface parameterization in graphics,registration in computer vision,and generative models in deep learning.For qua...Optimal transportation plays a fundamental role in many fi elds in engineering and medicine,including surface parameterization in graphics,registration in computer vision,and generative models in deep learning.For quadratic distance cost,optimal transportation map is the gradient of the Brenier potential,which can be obtained by solving the Monge-Ampère equation.Furthermore,it is induced to a geometric convex optimization problem.The Monge-Ampère equation is highly non-linear,and during the solving process,the intermediate solutions have to be strictly convex.Specifi cally,the accuracy of the discrete solution heavily depends on the sampling pattern of the target measure.In this work,we propose a self-adaptive sampling algorithm which greatly reduces the sampling bias and improves the accuracy and robustness of the discrete solutions.Experimental results demonstrate the efficiency and efficacy of our method.展开更多
基金supported by the Yuxiu Innovation Project of NCUT(Grant No.2024NCUTYXCX211).
文摘Purpose–This paper aims to provide a comprehensive analysis of the strategic adjustments in China’s transportation structure,with a particular focus on the pivotal role of railway freight and its integration into the modern logistics system.It seeks to address the need for a more nuanced understanding of the“road to rail”policy,emphasizing the importance of intermodal collaboration and service of fragmented market demands.Design/methodology/approach–The study employs a transport economics perspective to evaluate the achievements and shortcomings of China’s transportation structure optimization.It bases its assessment of the current state of railway freight logistics,multi-modal transportation and the broader implications for the transportation service market on data analysis.The methodology includes a review of existing policies,an examination of industry practices and a comparative analysis with global trends in railway logistics.Findings–The research underscores the importance of focusing on the development of non-bulk materials,noting the insufficiency in the development of China’s rail multi-modal transportation and highlighting the instructive value of successful cases in open-top container road-rail intermodal transportation.The study posits that the railway sector must enhance cooperation with other market entities,aligning with the lead enterprises in the logistics chain that are characterized by speed,high value and strong coordination capabilities,in order to better serve the transportation market.This approach moves away from a reliance on the railway’s own capabilities alone.Originality/value–This paper offers original insights into the transformation of railway freight in China,contributing to the body of knowledge on transportation economics and logistics.It provides valuable recommendations for policymakers and industry practitioners,emphasizing the strategic importance of railway logistics in the context of China’s economic development and intense competition in the supply chain.The value of the article lies in its comprehensive understanding of the complexities involved in the adjustment of transportation structures,providing direction for the market-oriented reform of China’s railway freight sector.
基金Supported by Heilongjiang Province Philosophy and Social Science Planning Research Project(22JYB232)。
文摘Rural vitalization is a major strategy for reform and development of agriculture and rural areas in China,the key task of which is improving rural living environment.Imperfect rural solid waste(RSW)collection and transportation system exacerbates the pollution of RSW to rural living environment,while it has not been established and improved in the cold region of Northern China due to climate and economy.Through the analysis of the current situation of RSW source separation,collection,transportation and disposal in China,an RSW collection and transportation system suitable for the northern cold region was developed.Considering the low winter temperature in the northern cold region,different requirements for RSW collection,transportation and terminal disposal,scattered source points and single terminal disposal nodes in rural areas,the study focused on determining the number and location of transfer stations,established a model for transfer stations selection and RSW collection and transportation routes optimization for RSW collection and transportation system,and proposed the elite retention particle swarm optimization–genetic algorithm(ERPSO–GA).The rural area of Baiquan County was taken as a representative case,the collection and transportation scheme of which was given,and the feasibility of the scheme was clarified by simulation experiment.
基金Supported by the Education Foundation of Hubei Province under Grant No D20120104
文摘We propose a self-organized optimization mechanism to improve the transport capacity of complex gradient networks. We find that, regardless of network topology, the congestion pressure can be strongly reduced by the self-organized optimization mechanism. Furthermore, the random scale-free topology is more efficient to reduce congestion compared with the random Poisson topology under the optimization mechanism. The reason is that the optimization mechanism introduces the correlations between the gradient field and the local topology of the substrate network. Due to the correlations, the cutoff degree of the gradient network is strongly reduced and the number of the nodes exerting their maximal transport capacity consumedly increases. Our work presents evidence supporting the idea that scale-free networks can efficiently improve their transport capacity by self- organized mechanism under gradient-driven transport mode.
基金supported by National Natural Science Foundation of China(11071119)
文摘This paper concerns the weak solutions of some Monge-Amp^re type equa- tions in the optimal transportation theory. The relationship between the Aleksandrov solutions and the viscosity solutions of the Monge-Ampere type equations is discussed. A uniform estimate for solution of the Dirichlet problem with homogeneous boundary value is obtained.
基金Project(71001079)supported by the National Natural Science Foundation of China
文摘A theoretical study was conducted on finding optimal paths in transportation networks where link travel times were stochastic and time-dependent(STD). The methodology of relative robust optimization was applied as measures for comparing time-varying, random path travel times for a priori optimization. In accordance with the situation in real world, a stochastic consistent condition was provided for the STD networks and under this condition, a mathematical proof was given that the STD robust optimal path problem can be simplified into a minimum problem in specific time-dependent networks. A label setting algorithm was designed and tested to find travelers' robust optimal path in a sampled STD network with computation complexity of O(n2+n·m). The validity of the robust approach and the designed algorithm were confirmed in the computational tests. Compared with conventional probability approach, the proposed approach is simple and efficient, and also has a good application prospect in navigation system.
基金Projects(71301115,71271150,71101102)supported by the National Natural Science Foundation of ChinaProject(20130032120009)supported by Specialized Research Fund for the Doctoral Program of Higher Education of China
文摘The traditional manner to design public transportation system is to sequentially design the transit network and public bicycle network. A new public transportation system design problem that simultaneously considers both bus network design and public bicycle network design is proposed. The chemical reaction optimization(CRO) is designed to solve the problem. A shortcoming of CRO is that, when the two-molecule collisions take place, the molecules are randomly picked from the container.Hence, we improve CRO by employing different mating strategies. The computational results confirm the benefits of the mating strategies. Numerical experiments are conducted on the Sioux-Falls network. A comparison with the traditional sequential modeling framework indicates that the proposed approach has a better performance and is more robust. The practical applicability of the approach is proved by employing a real size network.
基金supported by the National Natural Science Foundation of China (62206204,62176193)the Natural Science Foundation of Hubei Province,China (2023AFB705)the Natural Science Foundation of Chongqing,China (CSTB2023NSCQ-MSX0932)。
文摘When encountering the distribution shift between the source(training) and target(test) domains, domain adaptation attempts to adjust the classifiers to be capable of dealing with different domains. Previous domain adaptation research has achieved a lot of success both in theory and practice under the assumption that all the examples in the source domain are welllabeled and of high quality. However, the methods consistently lose robustness in noisy settings where data from the source domain have corrupted labels or features which is common in reality. Therefore, robust domain adaptation has been introduced to deal with such problems. In this paper, we attempt to solve two interrelated problems with robust domain adaptation:distribution shift across domains and sample noises of the source domain. To disentangle these challenges, an optimal transport approach with low-rank constraints is applied to guide the domain adaptation model training process to avoid noisy information influence. For the domain shift problem, the optimal transport mechanism can learn the joint data representations between the source and target domains using a measurement of discrepancy and preserve the discriminative information. The rank constraint on the transport matrix can help recover the corrupted subspace structures and eliminate the noise to some extent when dealing with corrupted source data. The solution to this relaxed and regularized optimal transport framework is a convex optimization problem that can be solved using the Augmented Lagrange Multiplier method, whose convergence can be mathematically proved. The effectiveness of the proposed method is evaluated through extensive experiments on both synthetic and real-world datasets.
文摘足球比赛场景中球员居多、足球目标偏小且移动速度快,足球检测识别难度很大。为了解决这一问题,提出一种基于改进的YOLOv5的足球检测方法,增加使用了OTA(Optimal Transport Assignment)损失函数来优化模型提高对足球目标的识别精度,最后在Roboflow的足球数据集上进行训练,对足球比赛场景下的足球进行目标检测实现足球识别。根据实验可以得出结论:改进后的YOLOv5算法的足球识别不仅提高了足球的识别性能与精度,而且有效地提高了检测速度,具有更好的识别性能。
文摘We propose a novel framework for learning a low-dimensional representation of data based on nonlinear dynamical systems,which we call the dynamical dimension reduction(DDR).In the DDR model,each point is evolved via a nonlinear flow towards a lower-dimensional subspace;the projection onto the subspace gives the low-dimensional embedding.Training the model involves identifying the nonlinear flow and the subspace.Following the equation discovery method,we represent the vector field that defines the flow using a linear combination of dictionary elements,where each element is a pre-specified linear/nonlinear candidate function.A regularization term for the average total kinetic energy is also introduced and motivated by the optimal transport theory.We prove that the resulting optimization problem is well-posed and establish several properties of the DDR method.We also show how the DDR method can be trained using a gradient-based optimization method,where the gradients are computed using the adjoint method from the optimal control theory.The DDR method is implemented and compared on synthetic and example data sets to other dimension reduction methods,including the PCA,t-SNE,and Umap.
基金the National Natural Science Foundation of China(61936002,61772105,61432003,61720106005,and 61772379)US National Science Foundation(NSF)CMMI-1762287 collaborative research“computational framework for designing conformal stretchable electronics,Ford URP topology optimization of cellular mesostructures’nonlinear behaviors for crash safety,”NSF DMS-1737812 collaborative research“ATD:theory and algorithms for discrete curvatures on network data from human mobility and monitoring.”。
文摘This work introduces an optimal transportation(OT)view of generative adversarial networks(GANs).Natural datasets have intrinsic patterns,which can be summarized as the manifold distribution principle:the distribution of a class of data is close to a low-dimensional manifold.GANs mainly accomplish two tasks:manifold learning and probability distribution transformation.The latter can be carried out using the classical OT method.From the OT perspective,the generator computes the OT map,while the discriminator computes the Wasserstein distance between the generated data distribution and the real data distribution;both can be reduced to a convex geometric optimization process.Furthermore,OT theory discovers the intrinsic collaborative-instead of competitive-relation between the generator and the discriminator,and the fundamental reason for mode collapse.We also propose a novel generative model,which uses an autoencoder(AE)for manifold learning and OT map for probability distribution transformation.This AE–OT model improves the theoretical rigor and transparency,as well as the computational stability and efficiency;in particular,it eliminates the mode collapse.The experimental results validate our hypothesis,and demonstrate the advantages of our proposed model.
基金supported by the National Natural Science Foundation of Unite States (Grants DMS-1620026 and DMS-1913163)supported by the National Natural Science Foundation of China (Grant 11601329)
文摘In this work,we develop an invertible transport map,called KRnet,for density estimation by coupling the Knothe–Rosenblatt(KR)rearrangement and the flow-based generative model,which generalizes the real-valued non-volume preserving(real NVP)model(arX-iv:1605.08803v3).The triangular structure of the KR rearrangement breaks the symmetry of the real NVP in terms of the exchange of information between dimensions,which not only accelerates the training process but also improves the accuracy significantly.We have also introduced several new layers into the generative model to improve both robustness and effectiveness,including a reformulated affine coupling layer,a rotation layer and a component-wise nonlinear invertible layer.The KRnet can be used for both density estimation and sample generation especially when the dimensionality is relatively high.Numerical experiments have been presented to demonstrate the performance of KRnet.
文摘Despite recent turbulences in global economy, the growth of global trade volumes is expected to continue in the future, leading to increased demands on the performance of logistics networks. The political framework for EU （European Union） Transport Policy Development is presented in the EU White Paper on Transport 2011 in order to build a competitive European transport system. One significant aspect is the promotion of multimodal transport in order to decrease terrestrial transport services （road and rail） and to increase services in the maritime transport sector, especially considering the relief of road and railway infrastructure. Looking at the present situation, SSS （Short Sea Shipping） is already used in many different transport fields all around the world. However, there still exists a great potential which currently is not used or not sufficiently exploited for many different reasons. In order to identify the potential use of SSS in multimodal transport, different scenarios in the Baltic Sea Region and the adjoining hinterland have been developed pointing out alternative solutions for routing. These options are analyzed in detail and evaluated from different perspectives （i.e. transport and handling costs, time consumption and transport-related emissions）. Afterwards, advantages and disadvantages of each alternative will be examined by taking into account economic and ecological aspects in making decision.
基金Supported by the National High Technology Research and Development Program of China(2014AA041803)the National Natural Science Foundation of China(61320106009)
文摘Low pressure chemical vapor deposition(LPCVD) is one of the most important processes during semiconductor manufacturing.However,the spatial distribution of internal temperature and extremely few samples makes it hard to build a good-quality model of this batch process.Besides,due to the properties of this process,the reliability of the model must be taken into consideration when optimizing the MVs.In this work,an optimal design strategy based on the self-learning Gaussian process model(GPM) is proposed to control this kind of spatial batch process.The GPM is utilized as the internal model to predict the thicknesses of thin films on all spatial-distributed wafers using the limited data.Unlike the conventional model based design,the uncertainties of predictions provided by GPM are taken into consideration to guide the optimal design of manipulated variables so that the designing can be more prudent Besides,the GPM is also actively enhanced using as little data as possible based on the predictive uncertainties.The effectiveness of the proposed strategy is successfully demonstrated in an LPCVD process.
文摘In this exposition paper we present the optimal transport problem of Monge-Ampère-Kantorovitch(MAK in short)and its approximative entropical regularization.Contrary to the MAK optimal transport problem,the solution of the entropical optimal transport problem is always unique,and is characterized by the Schrödinger system.The relationship between the Schrödinger system,the associated Bernstein process and the optimal transport was developed by Léonard[32,33](and by Mikami[39]earlier via an h-process).We present Sinkhorn’s algorithm for solving the Schrödinger system and the recent results on its convergence rate.We study the gradient descent algorithm based on the dual optimal question and prove its exponential convergence,whose rate might be independent of the regularization constant.This exposition is motivated by recent applications of optimal transport to different domains such as machine learning,image processing,econometrics,astrophysics etc..
文摘Despite of fluctuations in world trade as a result of economic cycles,the evolution of the political processes remains the trend of sustained growth of trade flows.This ends up in a rise in both the demand for logistics services and the requirements for them.In this sense,the critically important is the strategic development of the transport systems as a support for the improvement of competitive logistics.An important aspect is the promotion of multimodal transport,which in search of the best transport solutions will reduce the use of relatively expensive and environmentally unfriendly road transportation.This will be at the expense of the efficient combination of different modes in which the concept of short sea shipping(SSS)occupies a central place.Although this concept is widely applied in many places in the Black Sea,it still has significant potential.It was prompted by stagnation in economic relations as a result of political and economic crises in the region since the late twentieth and early twenty-first century.To evaluate the potential of the concept in the development of transport is done research on intermodal logistics network in the logistics corridor Central Asia-Central Europe.To optimize intermodal transport links a comparative analysis of the various transport alternatives on the route Tehran-Budapest is done.On this basis it is made optimization assessment on three main criteria cost,delivery time and environmental protection and basic recommendations on strategic planning development of the Bulgarian transport infrastructure are given.An essential aspect is the encouragement of multimodal transportation,which in looking for the best transport solutions can cut back the utilization of comparatively costly and environmentally harmful road transportation.This would be at the expense of the adequate combination of different modes of transportation in which the concept of SSS has a fundamental area.Despite this concept is widely applied in various regions,in the Black Sea it still has an important future due to stagnation in economic relations as a result of political confrontations and economic crises within the region since the late twentieth and early twenty-first century.To assess the capability of the concept in the development of transport is done research on intermodal logistics network in the logistics corridor Central Asia-Central Europe.To improve intermodal transport links a comparative analysis of the various transport options on the routes Astana-Budapest and Tehran-Budapest are made.On this basis it is proposed an optimization assessment on three main criteria cost,delivery time and environmental protection,and fundamental suggestions on strategic development of the Bulgarian transport infrastructure are proposed.
文摘Purpose–Under the dual pressure of resources and environment,many countries have focused on the role of railways in promoting low-carbon development of integrated transportation and of even the whole society.This paper aims to provide a comprehensive study on methods to improve railway energy efficiency in other national railways and achievements made by China’s railways in the past practice,and then to propose ways in which in the future China’s railways could rationally select the path of improving energy efficiency regarding the needs of the nation’s ever-shifting development and carry out the re-engineering for mechanism innovation in energy conservation and emission reduction process.Design/methodology/approach–This paper first studies other national railways that have tried to promote the improvement of railway energy efficiency by the ways of technology,management and structural reconstruction to reduce energy consumption and carbon emissions.Among them,the effect of structural energy conservation and emission reduction has become more prominent.It has become the main energy conservation and emission reduction measure adopted by foreign railway sectors.The practice of energy conservation and emission reduction of railways in various countries has tended to shift from a technical level to a structural one.Findings–Key aspects in improving energy efficiency include re-optimization of energy structure,reinnovation of energy-saving technologies and optimization of transportation organization.Path selection includes continuing to promote electrified railway construction,increasing the use of new and renewable energy sources,and promoting the reform of railway transportation organizations.Originality/value–This paper provides further challenges and research directions in the proposed area and has referential value for the methodologies,approaches for practice in a Chinese context.To achieve the expected goals,relevant supporting policies and measures need to be formulated,including actively guiding integrated transportation toward railway-oriented development,promoting innovation in energy-saving and emission reduction mechanisms and strengthening policy incentives,focusing on improving the energy efficiency of railways through market behavior.At the same time,it is necessary to pay attention to new phenomena in the railway industry for track and analysis.
基金supported by the National Key Research and Development Program of China under Grant No.2021YFA1003003the National Natural Science Foundation of China under Grant Nos.61936002 and T2225012.
文摘The long-tailed data distribution poses an enormous challenge for training neural networks in classification.A classification network can be decoupled into a feature extractor and a classifier.This paper takes a semi-discrete optimal transport(OT)perspective to analyze the long-tailed classification problem,where the feature space is viewed as a continuous source domain,and the classifier weights are viewed as a discrete target domain.The classifier is indeed to find a cell decomposition of the feature space with each cell corresponding to one class.An imbalanced training set causes the more frequent classes to have larger volume cells,which means that the classifier's decision boundary is biased towards less frequent classes,resulting in reduced classification performance in the inference phase.Therefore,we propose a novel OTdynamic softmax loss,which dynamically adjusts the decision boundary in the training phase to avoid overfitting in the tail classes.In addition,our method incorporates the supervised contrastive loss so that the feature space can satisfy the uniform distribution condition.Extensive and comprehensive experiments demonstrate that our method achieves state-ofthe-art performance on multiple long-tailed recognition benchmarks,including CIFAR-LT,ImageNet-LT,iNaturalist 2018,and Places-LT.
基金sponsored in part by the National Natural Science Foundation of China(No.71101109)the Open Fund of the Key Laboratory of Highway Engineering of Ministry of Education,Changsha University of Science & Technology(No.kfj120108)
文摘This study proposes a flexible timetable optimization method based on hybrid vehicle size model to tackle the bus demand fluctuations in transit operation. Three different models for hybrid vehicle, large vehicle and small vehicle are built in this study, respectively. With the operation data of Shanghai Transit Route 55 at peak and off-peak hours, a heuristic algorithm was proposed to solve the problem. The results indicate that the hybrid vehicle size model excels the other two modes both in the total time and total cost. The study verifies the rationality of the strategy of hybrid vehicle size model and highlights the importance of the adaptive vehicle size in dealing with the bus demand fluctuation. The main innovation of the study is that unlike traditional timetables, the arrangement of the scheduling interval and the corresponding bus type or size are both involved in the timetable of hybrid vehicle size bus mode, which will be more effective to solve the problem of passenger demand fluctuation. Findings from this research would provide a new perspective to improve the level of regular bus service.
基金supported by Research Centre for Integrated Transport Innovation,UNSW
文摘This paper addresses the transportation network design problem （NDP） wherein the dis- tance limit and en-route recharge of electric vehicles are taken into account. Specifically, in this work, the network design problem aims to select the optimal planning policy from a set of infrastructure design scenarios considering both road expansions and charging station allocations under a specified construction budget. The user-equilibrium mixed-vehicular traffic assignment problem with en-route recharge （MVTAP-ER） is formulated into a novel convex optimization model and extended to a newly developed bi-level program of the aggregated NDP integrating recharge facility allocation （NDP-RFA）. In the algorithmic framework, a convex optimization technique and a tailored CA are adopted for, respectively, solving the subproblem MVTAP-ER and the primal problem NDP-RFA. Systematic ex- periments are conducted to test the efficacy of the proposed approaches. The results highlight the impacts of distance limits and budget levels on the project selection and evaluation, and the benefits of considering both road improvement policy and recharge service provision as compared to accounting for the latter only. The results also report that the two design objectives, to respectively minimize the total system travel time and vehicle miles travelled, are conflicting for certain scenarios.
基金the National Numerical Wind Tunnel Project,China(No.NNW2019ZT5-B13)the National Natural Science Foundation of China(Nos.61907005,61772105,61936002,and 61720106005)。
文摘Optimal transportation plays a fundamental role in many fi elds in engineering and medicine,including surface parameterization in graphics,registration in computer vision,and generative models in deep learning.For quadratic distance cost,optimal transportation map is the gradient of the Brenier potential,which can be obtained by solving the Monge-Ampère equation.Furthermore,it is induced to a geometric convex optimization problem.The Monge-Ampère equation is highly non-linear,and during the solving process,the intermediate solutions have to be strictly convex.Specifi cally,the accuracy of the discrete solution heavily depends on the sampling pattern of the target measure.In this work,we propose a self-adaptive sampling algorithm which greatly reduces the sampling bias and improves the accuracy and robustness of the discrete solutions.Experimental results demonstrate the efficiency and efficacy of our method.
