Stability and stabilization of discrete T-S fuzzy time-delay system based on maximal overlapped-rules group

The problems of stability and stabilization for the discrete Takagi-Sugeno（T-S） fuzzy time-delay system are investigated.By constructing a discrete piecewise Lyapunov-Krasovskii function（PLKF） in each maximal overlapped-rules group（MORG）,a new sufficient stability condition for the open-loop discrete T-S fuzzy time-delay system is proposed and proved.Then the systematic design of the fuzzy controller is investigated via the parallel distributed compensation control scheme,and a new stabilization condition for the closed-loop discrete T-S fuzzy time-delay system is proposed.The above two sufficient conditions only require finding common matrices in each MORG.Compared with the common Lyapunov-Krasovskii function（CLKF） approach and the fuzzy Lyapunov-Krasovskii function（FLKF） approach,these proposed sufficient conditions can not only overcome the defect of finding common matrices in the whole feasible region but also largely reduce the number of linear matrix inequalities to be solved.Finally,simulation examples show that the proposed PLKF approach is effective.

Implications of the EU’s Inclusion of Maritime Transport in the Emissions Trading System for Shipping Companies

1.Introduction Maritime transport is the backbone of international trade.The amount of total international maritime trade in million tonnes loaded was 8408 in 2012 and had increased to 11076 by 2019,for an average annual increase of 3.12%.In early 2020,the world fleet contained 98140 ships of 100 gross tonnes and above with 2.06 million dead weight tonnage of capacity[1].The greenhouse gas(GHG)emissions from shipping activities are not negligible.According to the fourth GHG study commissioned by the International Maritime Organization(IMO),in 2018,global shipping emitted a total of 1056 million tonnes of carbon dioxide(CO_(2)),accounting for around 2.89%of global anthropogenic CO_(2) emissions[2].Due to the international nature of shipping,efforts to control CO_(2) emissions from ships are absent from the Kyoto Protocol and the Paris Agreement.In an attempt to phase out carbon emissions from shipping entirely,the IMO formulated a strategy to cut the total annual GHG emissions from shipping by at least 50%from their 2008 levels by 2050[3];however,no mandatory rules have been promulgated since the release of this strategy.

Study on the Recycling and Treatment of WEEE in China

This paper investigates the regulations, recycling and treatment of WEEE (waste electrical and electronic equipment) in China. An online survey about Chinese households’ treatment of WEEE is conducted. Optimization models are used to compare the performances of WEEE treatment in two different recycling networks. In the first network, WEEE is collected and sent by recycling stations to licensed WEEE recycling and treatment centers for testing and dismantling. In the second network, WEEE are tested and dismantled at small recycling workshops in residential districts, and then parts/components that require further processing are sent to licensed WEEE recycling and treatment centers. The performances of the two networks are analyzed with linear programming models. The results indicate that the second model is more effective with lower cost and higher recycling efficiency.

RepDNet:A re-parameterization despeckling network for autonomous underwater side-scan sonar imaging with prior-knowledge customized convolution

Side-scan sonar(SSS)is now a prevalent instrument for large-scale seafloor topography measurements,deployable on an autonomous underwater vehicle(AUV)to execute fully automated underwater acoustic scanning imaging along a predetermined trajectory.However,SSS images often suffer from speckle noise caused by mutual interference between echoes,and limited AUV computational resources further hinder noise suppression.Existing approaches for SSS image processing and speckle noise reduction rely heavily on complex network structures and fail to combine the benefits of deep learning and domain knowledge.To address the problem,Rep DNet,a novel and effective despeckling convolutional neural network is proposed.Rep DNet introduces two re-parameterized blocks:the Pixel Smoothing Block(PSB)and Edge Enhancement Block(EEB),preserving edge information while attenuating speckle noise.During training,PSB and EEB manifest as double-layered multi-branch structures,integrating first-order and secondorder derivatives and smoothing functions.During inference,the branches are re-parameterized into a 3×3 convolution,enabling efficient inference without sacrificing accuracy.Rep DNet comprises three computational operations:3×3 convolution,element-wise summation and Rectified Linear Unit activation.Evaluations on benchmark datasets,a real SSS dataset and Data collected at Lake Mulan aestablish Rep DNet as a well-balanced network,meeting the AUV computational constraints in terms of performance and latency.

全生命周期成本分析框架下的电动公交充电器部署和车队管理

尽管城市交通电气化快速发展,但电动公交车(EB)车队的系统规划和管理进展却很落后。本研究首先综述了影响新生EB系统的基本问题,包括充电站部署、电池尺寸、公交车调度和生命周期分析。目前,EB系统的规划和运行是按顺序进行的,公交车调度是在公交车队和基础设施部署完毕后进行的,这导致了资源利用率低和资源浪费。对此,本文提出了混合整数规划模型,以尽可能低的生命周期成本(LCC)整合充电站部署和公交车队管理,包括所有权、运营、维护和排放费用,从而缩小了最佳规划和运营之间的差距。进一步引入了分支定价算法,以减少寻找最佳解决方案所需的计算工作量。本研究还通过分析真实案例,与目前的公交运营策略和充电站布局相比,一条公交线路的LCC可显著降低30.4%。提出的研究不仅可以进行生命周期分析,还可以为交通当局和运营商提供可靠的充电站部署及单线和多线服务的公交时刻表,这两者都是未来具有高电气化普及率的交通系统中决策支持的关键要求,本研究也有助于推动可持续交通的发展。

海运数据驱动建模——关键问题、挑战和解决方案

1.Uncertainty in maritime transportation Maritime transportation plays a central role in global logistics systems.Over 80%of international trade is carried out via the maritime transportation network[1],which has received widespread attention from academia and industry.In the shipping network,ports are the vertices where large numbers of activities occur,including cargo loading,unloading,and transshipment.Ships sailing between different ports travel along routes that form the links of the network.Shipping operation studies usually cover ship routing,schedule design,fleet deployment,and network design.

Operation management of green ports and shipping networks: overview and research opportunities

Global ports and maritime shipping networks are important carriers for global supply chain networks, but they are also the main sources of energy consumption and pollution. To limit ship emissions in ports and offshore areas, the International Maritime Organization, as well as some countries, has issued a series of policies. This study highlights the importance and necessity of investigating emergent research problems in the operation management of green ports and maritime shipping networks. Considerable literature related to this topic is reviewed and discussed. Moreover, a comprehensive research framework on green port and shipping operation management is proposed for future research opportunities. The framework mainly comprises four research areas related to emission control and grading policies. This review may provide new ideas to the academia and industry practitioners for improving the performance and efficiency of the operation management of green ports and maritime shipping networks.

Paradox of international maritime organization's carbon intensity indicator

The 76th session of the Marine Environment Committee(MEPC 76)of the International Maritime Organization adopted several mandatory measures in June 2021 to reduce carbon emissions from ships.One of the measures is the carbon intensity indicator(CII),which is the carbon emissions per unit transport work for each ship.Several options of CIIs are available and none of them is chosen to be applied yet.We prove that,at least in theory,requiring the attained annual CII of a ship to be less than a reference value,no matter which CII option is applied,may increase its carbon emissions.Therefore,more elaborate models,combined with real data,should be developed to analyze the effectiveness of each CII option and possibly to design a new CII.

Emerging approaches applied to maritime transport research:Past and future

Maritime transport is the backbone of international trade and globalization.Maritime transport research can be roughly divided into two categories,namely the shipping side and the port side.Most of the classic approaches adopted to address practical problems in these research topics are based on long-term observations and expert knowledge,while few of them are based on historical data accumulated from practice.In recent years,emerging approaches,which we refer to as machine learning and deep learning techniques in this essay,have been receiving a wider attention to solve practical problems.As a relatively conservative industry,there are some initial trials of applying the emerging approaches to solve practical problems in the maritime sector.The objective of this essay is to review the application of emerging approaches to maritime transport research.The main research topics in maritime transport and classic methods developed to solve them are first presented.The introduction of emerging approaches and their suitability to be applied in maritime transport research is then discussed.Related existing studies are then reviewed according to problem settings,main data sources,and emerging approaches adopted.Challenges and solutions in the process are also discussed from the perspectives of data,model,users,and targets.Finally,promising future research directions are identified.This essay is the first to give a comprehensive review of existing studies on developing machine learning and deep learning models together with popular data sources used to address practical problems in maritime transport.

How do Normal Traders and Sharp Traders Make Profits in the Chinese Security Market?

In this paper,we consider the strategic interaction between the normal and sharp traders in a dynamic limit-order security market and its impact on the Chinese security market at different market volatility levels.We find that when the proportion of sharp traders is less than a threshold in an orderdriven market,the sharp traders who submit limit orders will get more returns than the normal traders.The participation of sharp traders in the market can increase the total social welfare of all the traders.In addition,we show that:(1)when the market volatility level is generally low,the short-term sharp traders benefit from larger volatility;(2)when the market volatility level is generally high,the insider/cheating sharp traders with high-frequent trading rather than the short-term sharp traders benefit from extreme high volatility;(3)when the market volatility level is moderate,the sharp traders can increase market liquidity.

Extreme Tenacity of Graphs with Given Order and Size

Computer or communication networks are so designed that they do not easily get disrupted under external attack and,moreover,these are easily reconstructible if they do get disrupted.These desirable properties of networks can be measured by various graph parameters,such as connectivity,toughness,scattering number,integrity,tenacity,rupture degree and edge-analogues of some of them.Among these parameters,the tenacity and rupture degree are two better ones to measure the stability of a network.In this paper,we consider two extremal problems on the tenacity of graphs:determine the minimum and maximum tenacity of graphs with given order and size.We give a complete solution to the first problem,while for the second one,it turns out that the problem is much more complicated than that of the minimum case.We determine the maximum tenacity of trees with given order and show the corresponding extremal graphs.The paper concludes with a discussion of a related problem on the edge vulnerability parameters of graphs.

Three potential benefits of the EU and IMO’s landmark efforts to monitor carbon dioxide emissions from shipping

International shipping accounts for around 2.2%of global carbon dioxide(C0_(2))emissions(Smith et al.,2014).Emissions from international shipping are expected to increase by 50%-250%by 2050,mainly due to the growth of the world maritime trade(Smith et al.,2014).However,efforts to control C0_(2)emissions from the global shipping industry are absent from the Kyoto Protocol and Paris Agreement.Therefore,the International Maritime Organization(IMO)has released an ambitious strategy to cut the total annual greenhouse gas emissions of shipping by at least 50%by 2050,compared with 2008(IMO,2018).

Data and Code Disclosure and Sharing Policy of communications in transportation research

1.Introduction Replicability is an essential requirement for scientific publications,as it ensures the high reliability and soundness of new scientific methods and discoveries.Replicability is particularly crucial for current research in Transportation Engineering,as most such research is built on sophisticated computational models and/or empirical/experimental data analyses.Examples include machine learning for demand/traffic state prediction and optimization;statistical and econometric models for traffic safety and travel behavior analysis;complex mathematical models and optimization approaches for transport planning,operation design,and controls;and numeric simulations.Because of the complexity of the mathematical methods and big traffic data,it is challenging to include all technical details(e.g.,all parameter settings of algorithms and simulation setups)in a manuscript.

Integrating operations research into green logistics:A review

Logistical activities have a significant global environmental impact,necessitating the adoption of green logistics practices to mitigate environmental effects.The COVID-19 pandemic has further emphasized the urgency to address the environmental crisis.Operations research provides a means to balance environmental concerns and costs,thereby enhancing the management of logistical activities.This paper presents a comprehensive review of studies integrating operations research into green logistics.A systematic search was conducted in the Web of Science Core Collection database,covering papers published until June 3,2023.Six keywords(green logistics OR sustainable logistics OR cleaner logistics OR green transportation OR sustainable transportation OR cleaner transportation)were used to identify relevant papers.The reviewed studies were categorized into five main research directions:Green waste logistics,the impact of costs on green logistics,the green routing problem,green transport network design,and emerging challenges in green logistics.The review concludes by outlining suggestions for further research that combines green logistics and operations research,with particular emphasis on investigating the long-term effects of the pandemic on this field.

Delivery Efficiency and Supplier Performance Evaluation in China's E-retailing Industry

This paper focuses on overall and sub-process supply chain efficiency evaluation using a network slacks-based measure model and an undesirable directional distance model. Based on a case analysis of a leading Chinese B2 C firm W, a two-stage supply chain structure covering procurementstock and inventory-sale management is constructed. The research shows overall supply chain inefficiency is attributable to procurement-stock conversion inefficiency. From a view of operations model,the third-party platform model is more efficient than a "shop in shop" self-operated model. However,the self-operated mode performs better in product categories such as computer & Office & digital, food& drink and healthy products due to these products' delivery characteristics and consumers' shopping habits. In the logistics selection, most e-retail players are inclined to choose the hybrid model of 3 PL and self-operated logistics with the product category extension from vertical model to all-category model. These findings may help managers improve supplier-buyer relationship and strengthen supply chain management. This research offers a new explanation regarding the failure of e-retail supply chain.

The Effect of Unannounced Inspection on Prevention of Drug Fraud

Alarge number of incidents related to fake/inferior-quality drugs have occurred in China in recent years. In order to reduce drug crimes, the China Food and Drug Administration (CFDA) has exploited the new supervision approach, i.e., unannounced inspection (UI), since September 2014. However, the effectiveness of UI in driving drug producers to put more effort into meeting the requirements of Good Manufacturing Practice (GMP) is yet to be ascertained. In this paper we apply game theory to study the effects of UI on the prevention of drug fraud, drug producers’ profits, and social welfare under scenarios of complete and incomplete information. We show that UI is not always an effective way of supervision. Specifically, if the upper bound on the punishment is not very large, UI can drive the firmto make the largest self-supervision effort only when the firm’s technical level is high and the supervision cost is low. Otherwise, UI cannot drive the firm to make the largest self-supervision effort. Under incomplete information, firms with a high technical level would adopt more self-supervision and make more profit than those with a low technical level. Moreover, we design a new mechanism under incomplete information that can incentive drug producers to make greater self-supervision effort to meet the requirements of GMP under certain conditions.

Evaluating returns to scale and congestion by production possibility set in intersection form

This research proposes a new method to estimate returns to scale(RTS) of decision making units(DM Us) with multiple inputs and outputs.The state of return to scale includes increasing RTS,constant RTS,decreasing RTS and evidence of congestion.The method is based on the production possibility set in the intersection form given by a set of linear inequalities.We propose and prove the necessary and sufficient conditions for the RTS estimation.With the new procedure,to estimate the RTS of a DM U is simply to check the position of the DM U on the production frontiers.We point out that the procedure is particularly important for dealing with a large number of DM U s.Therefore,it can be regarded as a complementary to the data mining.

Communications in Transportation Research:Vision and scope

Transportation is a vibrant,practical and public-oriented field that has undergone rapid and sustained growth.Traditionally,this growth was largely due to urbanization and increased trade and travel between countries and regions across the world.At most research universities worldwide,transportation engineering,as a sub-discipline under civil engineering,mainly analyses relationships among travelers,vehicles,transport infrastructure,and environment,using highly aggregated data(e.g.,origin-destination matrix,traffic volume,speed,density).In recent years,thanks to the rapid advancement in data collection and processing(e.g.,high-resolution individualized real-time data),vehicular technologies(e.g.,connected,automated and electric vehicles),and computational and communication enhancement(e.g.,real time automatic control,cloud and edge computing),transportation engineering keeps expanding its borders,encompassing more and more emerging interdisciplinary components(e.g.,shared mobility,modular vehicles,flying cars,hyperloop,boring).Not surprisingly,more and more researchers with a diverse background are involved in transportation related studies,including but not limited to computer science,mechanical engineering,electrical engineering,control engineering,psychology,urban planning,business,law.This is because transportation is essentially interdependent with a number of other large-scale systems,including electricity grid(e.g.,via electric vehicles),communication networks(e.g.,via connected vehicles),emergency management systems(e.g.,via emergency vehicles),and even societal systems(e.g.,via residential development and house valuation),which overhauls human mobility/travel behaviors,infrastructure systems,and societal awareness.Indeed,our next generation urban mobility system will become a system of multiple systems.We believe that the future transport discipline can be characterized as an inter-disciplinary system of systems with emerging components that are enabled and empowered by huge amount of data that are collected,communicated,and processed in real time and in various forms.This journal Communications in Transportation Research(COMMTR)is focused on the above characteristics.

Is uncertainty always bad for the performance of transportation systems?

Uncertainty is usually perceived as having negative effects on transportation systems,such as increasing operation cost,decreasing resource utility,and reducing customer satisfaction.However,it is unclear whether this perception is universally true or is true only under certain conditions.This research compares the performance of transportation systems with uncertain parameters with the performance of the same systems in which the uncertain parameters are replaced by their expectations.The analyses prove that uncertainty can have negative,negligible,and positive impact on the performance of transportation systems under different conditions.

Evaluating Efficiency of Decision Making Units with Network Structures

This paper considers the problem of evaluating efficiency of Decision Making Units （DMUs） with network structures of divisions by the Data Envelopment Analysis （DEA） model. All divisions in the network are under a decentralized authority organiza- tion. That is, each division in a decision making unit has its own authority to adjust its input and output. By incorporating the division operations in the DEA model, we discuss the sufficient and necessary conditions for a DMU to be network efficient in series structure and general structure respectively.