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With the deepening of green and sustainable development and the rapid development of the social economy, the modern logistics industry has also developed to an unprecedented level. In the logistics supply chain, due to the high value of the items inside the arrival carton, appearance inspection must be carried out before warehousing. However, manual inspection is slow and ineffective, resulting in the waste of manpower and packaging carton resources, which is not conducive to sustainable development. To address the above problems, this paper designs a logistics supply chain carton packaging quality defect detection system based on improved Single Shot MultiBox Detector (SSD) in the context of green sustainable development. The Implicit Feature Pyramid Network (IFPN) is introduced into SSD to improve the feature extraction ability of the model; the multiscale attention mechanism is introduced to collect more feature information. The experiment shows that the mAP and FPS of the system on the self-built data set reach 0.9662 and 36 respectively, which can realise the detection of the appearance defects of logistics cartons and help promote green sustainable development. [ABSTRACT FROM AUTHOR]

The logistics industry plays a crucial role in facilitating regional economic development. Serving as a vital link connecting producers, consumers, and various components of the supply chain, it has a direct and profound impact on the prosperity and advancement of regional economies. Based on the panel data of 11 provinces in the Yangtze River Economic Belt from 2016 to 2020, this paper constructs the logistics capability evaluation index system from four aspects: regional economic base, logistics infrastructure, logistics development scale, information technology and talent support, and uses the entropy weight TOPSIS method to measure the logistics capability of each province. The adjacency space weight matrix, geographical distance weight matrix and economic distance weight matrix are selected to build a spatial econometric model to analyze the influencing factors and spatial spillover effects of regional logistics capability. The following conclusions can be drawn from the analysis. From 2016 to 2020, the regional logistics capacity of the Yangtze River Economic Belt shows a trend of increasing year by year, but the logistics capacity of different provinces within the region has a large room for improvement. From the perspective of spatial dimension, the logistics capacity of the Yangtze River Economic Belt is "high in the east and low in the west". The results of spatial econometric analysis based on the spatial Durbin model show that there are significant spatial spillover effects on the logistics capacity of provinces in the Yangtze River Economic Belt. Factors such as road network density, port throughput, water freight turnover, transportation, warehousing and postal employment will not only affect the logistics capacity of the region, but also have a spillover effect on the material capacity of neighboring provinces in the Yangtze River Economic Belt. This study improves the level of regional logistics capacity and promotes the regional economic development of the Yangtze River Economic Belt. It can be used as a reference for other regions or countries in terms of enhancing regional logistics capacity and promoting regional economic development. [ABSTRACT FROM AUTHOR]

While the idea of autonomous vehicles has been enthusiastically embraced by scientists and commercial markets alike, ranging from solving the last mile problem across shared economy models in various segments to human transportation logistics, more than just a few aspects require further development before driverless urban logistics can be organized more thoroughly and meaningfully for our practical purposes. Before fully autonomous vehicles become standard, many of these shortcomings can be addressed (in part) by the remote operation of vehicles. Besides the various technological challenges, remote operation of vehicles also has many important legal and economic implications, impacting a wide area, including data protection, liability for torts performed, and mundane fields such as road traffic law. Based on a case study of a start-up developing remote operation solutions in Germany (Vay), this paper analyses and further develops the regulatory framework of remote operation solutions by highlighting their legal and economic implications. Since remote operation solutions are comprised of cyber-physical systems, this research is located in the context of Smart Cities and Industry 5.0, i.e., our research contributes to the related regulatory framework of the Smart City concept as well as to Industry 5.0 in international terms. Finally, the paper discusses future perspectives and proposes specific modes of compliance. [ABSTRACT FROM AUTHOR]

The construction of major railway projects poses significant risks, which present considerable challenges to construction management. To accurately assess the level of construction management for these projects, this study incorporated resilience theory into the field. The grounded theory method was utilized to establish a resilience evaluation indicator system for managing a major railway project construction. Additionally, a resilience evaluation model based on the Analytic Hierarchy Process (AHP) and fuzzy comprehensive evaluation method was proposed. This model was applied to evaluate the construction management resilience of a major railway project located in the mountainous region of southwest China. The results indicated that the project exhibits a very high overall level of construction management resilience. Specifically, it demonstrates high levels of ability to monitor and warn, an ability to resist absorption, and an ability to respond to emergencies. Additionally, it showcases high levels of ability to recover and rebuild, and an ability to learn to adapt. The evaluation results were consistent with the actual situation and verified the correctness and reliability of the method. Based on the aforementioned research findings, this paper puts forward recommendations on material redundancy and resource security from a resource perspective, and suggestions on organizational optimization and personnel capacity improvement from a subject perspective, thus indicating directions for enhancing the management level of major engineering railway constructions. [ABSTRACT FROM AUTHOR]

At present, there is still a lack of relevant theoretical guidance on the deployment of roadside RSU on expressways. In the face of the coexistence of V2V and V2I communication in the future, the deployment adjustment after the penetration of intelligent vehicles is not considered. Therefore, this paper proposes a roadside RSU deployment income model in consideration of the influence of V2V and V2I communication. Based on the optimal income of roadside RSU nodes, it achieves the optimization of the RSU deployment range and determines the optimal deployment spacing through the forwarding and relaying role of V2V communication so as to achieve cost savings. In terms of RSU coverage of positive income, it considers the impact of intelligent vehicles and reconstructs the traditional information flow–traffic flow coupling theory to innovatively realize the modeling of income within the information life cycle. In terms of the information transmission deficit, the WSN node energy loss model is reconstructed with permeability. Also, in terms of the construction and maintenance costs, the cost models are constructed for different cluster lengths. In order to provide a basis for expressway sensor network deployment, MATLAB software (version R2016B) is used to analyze the three-dimensional relationship between expressway traffic density, intelligent vehicle permeability, and roadside RSU deployment spacing as well as to determine the optimal roadside RSU deployment spacing with the income model. Finally, the model reliability is validated by the Warshell algorithm and the Kmeans clustering algorithm. [ABSTRACT FROM AUTHOR]

Forward guidance is widely considered a useful tool for improving monetary policy transmission. This paper introduces endogenous Delphic guidance in which future policy targets are time-varying and dependent on the future economy. The results show that the performance of inflation-targeting forward guidance depends partially on the forward horizon and the agents' expectation, while announcing an interim output target could stimulate the economy only under a rational expectation environment and requires a short forward horizon. We also discuss the effectiveness of Odyssean forward guidance which incorporates monetary authorities' preferences. The results indicate that the effect of a commitment on future paths of an interest-rate rule is based on the agents' expectations. [ABSTRACT FROM AUTHOR]

Intelligent vehicular networks can not only connect various smart terminals to manned or unmanned vehicles but also to roads and people's hands. In order to support diverse vehicle-to-everything (V2X) applications in dynamic, intelligent vehicular networks, efficient and flexible routing is fundamental but challenging. Aimed to eliminate routing voids in traditional Euclidean geographic greedy routing strategies, we propose a hyperbolic-embedding-aided geographic routing strategy (HGR) in this paper. By embedding the network topology into a two-dimensional Poincaré hyperbolic disk, greedy forwarding is performed according to nodes' hyperbolic coordinates. Simulation results demonstrated that the proposed HGR strategy can greatly enhance the routing success rate through a smaller stretch of the routing paths, with little sacrifice of routing computation time. [ABSTRACT FROM AUTHOR]

In the rapidly evolving global marketplace, the logistics sector faces a multitude of challenges that demand implementation of more resilient solutions to respond to any future disturbance. Synchromodal transport, which is viewed as an extension of multimodal transport, is known as a key answer to this issue, as it provides more flexible and sustainable freight transport and also focuses on collaboration between different logistics players. We consider synchromodal transport as a collection of agents that not only have their own characteristics and behaviors, but also interact with each other, which impacts the entire system. In this paper, we study the system using an Agent-Based Modeling approach. The network represents the combination of long-haul and drayage transport, where pre-haulage and end-haulage are done only by truck, and the rest can be done by trucks, trains, or barges. A numerical experiment is conducted to evaluate cost savings and emissions reduction under different logistics service providers' relation and re-routing scenarios. Our findings show that synchromodal scenarios are more economically and environmentally efficient, and that they lead to higher flexibility and reliability compared to business-as-usual scenarios. Additionally, our model verifies that the cost saving is considerable when logistics service providers collaborate with each other. The results of sensitivity analyses show consistent overall trends when comparing the different scenarios. Therefore, the conclusions drawn from the original experiment appear to be applicable, not only for that specific instance, but have broader relevance and applicability. [ABSTRACT FROM AUTHOR]

As a key component of high‐performance switches and routers, the packet forwarding engine (PFE) is mainly responsible for selecting the appropriate output port for tens of thousands of packets within an extremely short time frame. However, the performance of PFE is determined by the selected group membership algorithm. This paper puts forth a hybrid strategy–caching scalar‐pair and vectors routing and forwarding (CSVRF), consisting of virtual output port bitmap caching (VOPBC) and fractional‐N SVRF to address major multicast forwarding issues such as scalability by using content addressable memory. In CSVRF, a virtual output port bitmap cache is introduced, which includes the most popular combinations of output port bitmap and divides the big scalar‐pair into N sub‐groups to achieve parallel compute and the reusability of less bit‐length prime. The results demonstrate that the memory space and the forwarding latency are effectively reduced compared with previous work. In space efficiency, it only required 10% memory space compared with the original SVRF/fractional‐N SVRF, decreased 10% memory usage compared with pure VOPBC and nearly improved 1 to 4 orders of magnitude of packet processing time compared with the original SVRF and the fractional‐N SVRF respectively. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to explore how a start-up entering maritime logistics networks (MLNs) in the container shipping industry integrates resources underlying value cocreation patterns in these networks. Design/methodology/approach: The paper is based on a single case study of a technological start-up, providing tracking, tracing and other information services to MLN members using internet-based software. An interorganizational theory perspective informs the case study to unveil the resource integration for value cocreation in the network. Findings: The start-up holds multiple resource interaction roles and the start-up's involvement enables the creation of new knowledge resources, which facilitate new revenue streams and manage resource dependencies. Hence, the findings indicate that the start-up changes value cocreation patterns in the network by reconfiguring and integrating existing resources so that the service is customized for various customers, including shippers and freight forwarders. Practical implications: The results provide insights about how technological start-ups can unlock resources within MLNs. Originality/value: The study extends previous studies on resource roles in business networks and shows how start-ups can perform multiple roles simultaneously within these networks. In addition, the study contributes to the literature by studying information and knowledge as resources configured in different ways in a unique network setting. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of deciding the locations of dry ports by providing an intermodal rail-road p-hub median model, adopting a bi-level programming approach. In the proposed model, direct transportation and shipment between nodes are allowed instead of transportation merely through the hubs. In the bi-level programming approach, at the top level, the government/authority will decide the locations of the dry ports to increase the utilization of railways and minimize the construction and maintenance costs of dry ports as one of the important transportation infrastructures. Freight forwarders who are considered at the lower level aim to minimize the shipping costs by deciding the optimal shipping routes. A matheuristic approach based on the Genetic Algorithm (GA) is proposed to solve the given problem. Numerical analysis confirms that the proposed algorithm can provide satisfactory solutions for large instances where commercial solvers are not capable of finding the near optimal solutions in a reasonable computational time. Finally, the experimental results show that using the proposed transportation network model can decrease the total transportation costs along with significantly reduction of air pollution. [ABSTRACT FROM AUTHOR]

Urban logistics is important to a city's sustainable growth and development. With the increase in population and the economic growth in urban areas, the issue of congestion and the negative influence of transport of goods on people and the environment is one of the most important factors in the development of urban logistics. By determining the optimal location of urban logistics centres, total transport costs of logistics, the flow of goods in urban areas and the greenhouse gas emissions will be reduced. However, the traditional methods are easily influenced by the ambiguity of objective data, which makes it difficult to accurately describe the logistics demand in the urban area. To address this issue, the improved location–allocation model for urban logistics centres based on truck trajectory data is proposed. After extracting the origin–destination points, the logistics service demand can be estimated by the DBSCAN (density-based spatial clustering of applications with noise) clustering method. Then, the location–allocation of logistics centres is determined by an improved P-median method with the supply capacity limitation for simultaneous delivery of goods in the logistics centres. To validate the model, taking Wuhan, a central logistics city in China, as an example, the model can effectively ensure the equitable distribution of logistics facilities, minimize freight expenses, achieve more uniformity in logistics center services, and foster sustainable development of the city's logistics sector. [ABSTRACT FROM AUTHOR]

The paper deals with the interaction between freight flows, land use, and economy of a suburban area. In urban freight distribution, the process of freight acquisition of commercial establishments represents a crucial element. Therefore, it is necessary to plan city logistics in order to reduce the negative externalities generated by freight transport without depressing the economic and social vitality. In order to estimate and evaluate the performance and impacts generated by urban freight distribution, Transport System Models (TSMs) play an important role in reproducing and forecasting the process of distribution of final products to retailers and consumers. In recent years, Information and Communication Technologies (ICTs) have made new sources of data in great amounts available at lower costs than data provided from traditional surveys. Among the different data sources, Floating Car Data (FCD), obtained through GPS trackers installed on board the vehicles, offer partial insights into the examined process with lower cost and provide continuous information in space and time. In order to obtain reliable results, it is necessary to combine TSMs and ICTs as observed data could feed Transport System Models and could allow their calibration and therefore their application in real cases. In the above context, the paper deals with TSMs related to estimating urban freight demand flows. The work carried out concerns the specification-calibration-validation of a freight zonal acquisition model by means of FCD related to interzonal trips of commercial vehicles inside the Locride area (Reggio Calabria, Italy). The obtained models, estimated from FCD, could support the a priori evaluation of city logistics measures. The results are more important considering that they are obtained in an area with a lack of transport monitoring technologies. They could be adopted in other similar areas and confirm that adequate planning of city logistics determines advantages for environmental, social, and economic sustainability. [ABSTRACT FROM AUTHOR]

An increasing number of devices and their communication with each other generates huge amounts of data. The efficiency of processing such large and heterogeneous data is crucial for extracting the reliable and consistent information that is needed for the effective management of smart cities within the field of transport. Data heterogeneity and volume as well as its integration and analytics are big challenges for decision-makers. The development of urban agglomerations is largely dependent on the proper management of such data. Therefore, this paper explores the role of these data repositories, their acquisition from different sources, and the ways to combine them. The main goal of this paper is to propose a concept of Smart City management based on Big Data Analytics and technology related to UAVs (Unmanned Aerial Vehicle) which may reduce costs and resource consumption. The presented concept includes successive data generation and collection, data type identification, problem and requirement identification, filtering, classification, pre-processing, and data optimization, as well as decision support analysis. A key part of this analysis utilizes computer algorithms, such as Speeded Up Robust Features (SURF) and Thresholding and Blob detection, to develop a multi-camera image recognition system for freight transport management and logistics in smart cities. The objective is to design a system that optimizes the route planning and time of vehicle passage on selected road sections, ultimately leading to the reduction of emissions. During the study, data obtained from multiple sources were compared, and the analysis uncovered different results for the same assumptions. We discuss the reasons for these variances. Overall, the results obtained in the analysis indicated that it is necessary to correct the predictions of the multi-camera image recognition system with additional methods and algorithms. [ABSTRACT FROM AUTHOR]

Data analysis of weather phenomena to either predict or control human imprint on the environment requires the collection of various forms of observational data ranging from historical and longitudinal to forecast. The objective of this research paper is the development of a data warehouse (DW) based on a new hybrid logical schema, concerning the assimilation and maintenance of historical meteorological data from all operating airports in Greece, along with data in the Greek Flight Information Region related to flight delays and cancellations. SQL is used for querying these data and makes them easily accessible and manageable. The data from the DW are collected and used as training data for the induction of predictive models. In this study, the prediction problem is cast as a classification task, and different decision tree induction techniques are applied to build accurate models that allow flexible scheduling and planning for the minimization of waiting time and inconvenience of passengers. [ABSTRACT FROM AUTHOR]

The primary objective of an energy management strategy is to achieve optimal fuel economy through proper energy distribution. The adoption of a fuzzy energy management strategy is hindered due to different reasons, such as uncertainties surrounding its adaptability and sustainability compared to conventional energy control methods. To address this issue, a fuzzy energy management strategy based on long short-term memory neural network driving pattern recognition is proposed. The time-frequency characteristics of vehicle speed are obtained using the Hilbert–Huang transform method. The multi-dimensional features are composed of the time-frequency features of vehicle speed and the time-domain signals of the accelerator pedal and brake pedal. A novel driving pattern recognition approach is designed using a long short-term memory neural network. A dual-input and single-output fuzzy controller is proposed, which takes the required power of the vehicle and the state of charge of the battery as the input, and the comprehensive power of the range extender as the output. The parameters of the fuzzy controller are selected according to the category of driving pattern. The results show that the fuel consumption of the method proposed in this paper is 5.8% lower than that of the traditional fuzzy strategy, and 4.2% lower than the fuzzy strategy of the two-dimensional feature recognition model. In general, the proposed EMS can effectively improve the fuel consumption of extended-range electric vehicles. [ABSTRACT FROM AUTHOR]

This paper makes a systematic analysis of the automotive inbound logistics, and integrates the automotive inbound logistics system and the production system by rationalizing the three main links of the logistics, taking the theory of value chain increment as the guide, and using the idea of station marshalling driving. This paper integrated and optimized three main links of inbound logistics, constructed the optimization mode of automotive inbound logistics driven by station feeding marshalling and its supporting system. In the Work-Station Marshalling-Driven Automotive Inbound Logistics Mode, we construct a mathematical model and design a hybrid genetic algorithm that combines a local search algorithm and a genetic algorithm. And at the end the validity and practicality of this research is demonstrated by real-life examples. [ABSTRACT FROM AUTHOR]

The application of Internet of Things technology in cold chain transportation can greatly strengthen the monitoring of all aspects of cold chain logistics, so as to promote the progress of cold chain logistics industry. In order to study this aspect, this paper chooses the key link of the Internet of Things as a breakthrough. By analyzing various aspects of the transportation process, an Internet of Things middleware framework serving cold chain transportation tracking is designed. The main products of logistics cold chain transportation are fresh agricultural products, so in order to further make the research fit the actual situation, this paper collects the logistics data and information of agricultural products through investigation and combines the core technology of agricultural products logistics with the Internet and the key technology of cold chain transportation to process the obtained information. The analytic hierarchy process and fuzzy comprehensive evaluation method are used in this process. The processing results prove the validity and rationality of the established index system. The purpose of developing the international trade management system is to enable the company to optimize its international trade management process, reduce some tedious and inconvenient manual operations, make the recording and statistics of international trade information very simple, improve work efficiency, and satisfy the information needs of various departments to enable enterprises to minimize costs, thereby enabling enterprises to obtain better economic benefits. [ABSTRACT FROM AUTHOR]

UAVs in most real-world deployments communicate with a ground control station either in a one-hop manner, which has a limited working range, or relies on infrastructure support such as satellite communication, which is expensive. Although multi-hop transmission is more economic, it is lossy and generally incurs large delays. In this paper, we consider a mixed method, where a few UAVs are equipped with satellite modules, and aggregate and forward traffic of nearby UAVs. The surrounding UAVs and the forwarding UAV form a star topology. Based on this model, we design an UAV formation strategy to cover a given region to minimize both the total number of UAVs and the number of UAVs with satellite modules. Since these two goals may be competing, we propose seven strategies and analyze them theoretically. Simulations show that a good tradeoff between the two goals can be obtained when each star network consists of four UAVs. [ABSTRACT FROM AUTHOR]

Road freight transport involves many adversities, along with the growing effect of carbon dioxide transmitted by vehicles on the natural environment, greenhouse gas emissions, or extensive energy use. Within the smart mobility concept, the acknowledged management of enterprises' relationships with customers within their service is profoundly determined by the deployment of compelling Intelligent Transportation Systems (ITSs) applications in forming united cooperation with the customers. The paper proposes selected ITS applications as an advancement of logistics customer service in road freight transport enterprises that is divided into a group of six applications which are critical within the area of vehicle support, improving the energy efficiency of transport and reducing the negative impact of transport on the natural environment, reducing transport time but increasing connectivity and comfort, as well as a group of ten different applications chosen as crucial for general management support and increasing accessibility, cohesiveness, and control in management processes in road freight transport enterprises. The study also presents the effect of ITS applications on logistics customer service as dependent on an alignment between the group of ITS applications and logistics resources of road freight transport enterprises. The model proposed in the paper was analyzed based on the survey data obtained from 164 road freight transport enterprises in Poland. [ABSTRACT FROM AUTHOR]

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Maritime supply chain (MarSC) stakeholders interact with third parties (e.g. freight forwarders, 3PLs, financial institutes, custom authorities) to facilitate the cargo flow and exchange of information, documents, or financials. Hence, MarSC stakeholders are increasingly interested in innovative technological solutions that vouch for the authenticity and/or the ownership of digital assets without the control of a central third party. Extended research is carried out to prove how applications based on the distributed ledger technology or blockchain address these requirements, yet limited research investigates their purchasing process and economic implications. This paper uses the phytosanitary certificate in an international supply chain flow as a case study where interaction between multiple stakeholders is fundamental and analyses the purchase scenarios of a blockchain-based tool. To do so, it uses a theoretical model that identifies and quantifies the costs and benefits incurred by MarSC stakeholders, formulates gain-sharing scenarios and presents the results of a sensitivity analysis to show the dependence between the data-use and the potential economic gains it generates. The results show that freight forwarders could share economic benefits with shippers or consignees to anticipate purchasing a blockchain-based tool. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to improve service quality of international freight forwarders and explore practical business solutions to enhance customer service level. Freight forwarder usually acts as an agent to source logistics service for shipper and work closely with carriers such as shipping line and airline companies. This business is characterized by lower capital investment and entry barrier comparing with carriers, and most of their major customers are small or medium size manufactures or traders. Providing high quality service to enhance customer satisfaction is the key mission since competition is extremely severe. This paper empirically investigates the leading freight forwarders to find important customer requirements in East Asian region such as Japan, Korea and Taiwan. Furthermore, the feature of the study by using quality function deployment approach would not only identify key technical measures but also explore meaningful business solutions as direction of quality improvement. The finding reveals key customer requirements are cheaper agency fees, door to door ability and instant response, and the key technical measures are customer relationship management, overall information system, service point and network. We would further discuss the empirical result and conclude managerial meaning for decision makers. [ABSTRACT FROM AUTHOR]

Purpose: Nowadays, companies have required new alternatives and strategies to handle environmental sustainability difficulties, primarily as ecological and social awareness has grown. In this context, the aim is to determine the green transportation indicators in companies with corporate identity and logistics activities at the international level in Giresun, Ordu, Gümüshane, Artvin, Rize, and Trabzon in the Eastern Black Sea Region in Turkey. At the same time, the study contributes to providing an effective and applicable solution to decision-making problems involving the assessment of green transportation indicators and smart network strategies in the logistics sector, which is a critical sector for countries. The purpose of this paper is to address these issues. Design/methodology/approach: This study aims to propose a model for the selection of smart network strategy and to determine the criteria weights used in green transportation indicators, and establish an ideal smart network strategy. In achieving the outlined goals of the study, the authors believe that the model proposed in the study will draw the focus to green logistics which will aid the environmental, economic and social efforts of businesses and governments through the provision of efficient use of scarce resources, which will, in turn, ensure that we leave a sustainable environment for future generations and businesses enjoy a competitive advantage. At the same time, different smart network strategies and green transportation indicators in companies show the success rate of social, economic and environmental indicators in green logistics practices. In addition to providing innovative, reliable and sustainable transportation systems, smart network strategies are critical for businesses to create cost advantages. Through the green transportation indicators and smart network strategies selection model outlined in this study, it is clear that the contribution will not only be limited to businesses, as the society and governments will also benefit from the important indicators on sustainability, as well as the protection of the environment and nature. Findings: According to the findings, "economic indicators" is the essential green transportation indicator in logistics companies with a corporate identity and worldwide transportation operations. Besides, the "mixed access model strategy" is the most appropriate smart network strategy in logistics firms with corporate identity and worldwide transportation activities. Currently, it is possible to assume that logistics organizations prefer to profit from all smart network strategies in terms of cost optimization and competitiveness rather than from just one. The study, on the other hand, which is a road map that will help sustainability practices in the logistics sector due to green transportation, also examines the similarities and differences of green transportation practices in companies in the relevant sector and to what extent they can be reflected. As a result, the study provides a practical road map for selecting green transport indicators and a smart network strategy process for the logistics industry. Originality/value: This study examined logistics companies with a corporate identity and international transportation activities in provinces in the Eastern Black Sea Region such as Ordu, Giresun, Trabzon, Rize, Artvin and Gümüshane. Novel picture fuzzy level based weight assessment (PF-LBWA) and picture fuzzy combined compromise solution (PF-CoCoSo) methods are developed to solve the decision-making problem. [ABSTRACT FROM AUTHOR]

Tracking and tracing systems have become basic services for most logistics companies and are particularly essential for the shipping and logistics industry. Dynamic logistics management today need constant supervision and management of continuously-changing supply chains that motivate the necessity of goods-centric logistics monitoring and tracking, which guarantees a chance to improve transparency and control of a company’s multiple logistical activities. However, operational inefficiencies due to the conventional monitoring system for the supply chain management can also result in sales loss, higher cost, poor customer service–and eventually lower profits. Based on research literature, this paper aims to provide a novel approach for tracking and tracing shipment in a logistics organisation by implementing deep natural language processing concepts. The study aims to allow the stakeholders to think in new ways in their organisation and helping them to have a powerful influence on tracking and tracing to make the best decision possible at the right time. The proposed method is compared based on the accuracy of identifying the query, and results are significantly acceptable. This study is of related interest to researchers, academicians, and practitioners. [ABSTRACT FROM AUTHOR]

The automotive industry has to deal with wide-reaching challenges and changes. A continuous gain of significant competitive advantages in a highly competitive market requires automotive manufacturers to produce new products with a large diversity of variants at ever-shorter time intervals. As a result, the frequency of series launches has increased and the need for a sophisticated vehicle project management and an efficient handling of vehicle changes and model updates along the product process have gained significant importance. However, current project management practices and frameworks utilized by automotive manufacturers do not effectively address this demand, e.g., the goals of increasing operational efficiency and productivity as well as establishing continuous improvement are not sufficiently achieved. While these goals are traditionally common-place in certain fields of the automotive manufacturing, e.g., in production, logistics, or warehousing, their dedicated consideration in the vehicle project management or one of its neighboring areas like the vehicle change management has not been examined thoroughly in the required extend. Understanding the determinants of the needed change in the vehicle project management and its related fields is a central objective of the research presented in this paper. In this context, this paper proposes a novel approach on how to manage the transition and why this is a challenge to common project management practices utilized traditionally in the automotive industry. [ABSTRACT FROM AUTHOR]

With the rapid evolution of network technologies over recent years, emerging network services, especially industrial control networks, video conferencing, intelligent driving, and other scenarios, have put forward higher demand for the low-latency forwarding of network traffic. The existing flow caching and hardware acceleration methods only improve the overall forwarding performance of data-plane devices but cannot separate the forwarding process of low-latency traffic from others to reflect the priority of these flows. In this paper, we extend the POF southbound interface protocol and propose a marking method for low-latency flows, based on which we design a composite pipeline to achieve fast processing for low-latency traffic by introducing a fast-forwarding path. The experiments show that the fast path has a higher forwarding capability than the MAT pipeline in the POF Switch and can reduce the forwarding delay of low-latency flows by 62–68%. In a real network environment with a mixed traffic simulation, the reduction reaches 17–20% with no delay increment for the non-low-latency part. [ABSTRACT FROM AUTHOR]

In vehicular ad hoc networks (VANETs), efficient data dissemination to a specified number of vehicles with minimum collisions and limited access delay is critical for accident prevention in road safety. However, packet collisions have a significant impact on access delay, and they may lead to unanticipated link failure when a range of diversified collisions are combined due to complex traffic conditions and rapid changes in network topology. In this paper, we propose a distributed contention-free cooperative medium access control (CFC-MAC) protocol to reduce heterogenous collisions and unintended access delay in stochastic traffic scenarios. Firstly, we develop a cooperative communication system model and cooperative forwarding mechanism to explore the optimum road path between the source and destination by identifying the potential cooperative vehicles. Secondly, we propose a vectorized trajectory estimation mechanism to suppress merging collisions by identifying the relative velocity of vehicles with different speeds in a specific time interval. Based on the case study, typical heterogeneous collisions and aggregated heterogeneous collisions at dissociated positions and associated positions are investigated. In both cases, we propose the corresponding collision-resolving mechanisms by methodically recapturing the colliding time slot or acquiring the available free time slots after identifying the access vehicles and comparing the received signal strengths. Performance analysis for collision probability and access delay is conducted. Finally, the simulation results show that the proposed protocol can achieve deterministic access delay and a minimal collision rate, substantially outperforming the existing solutions. [ABSTRACT FROM AUTHOR]

Recently, the rapid development of software-defined networking (SDN) and programming protocol-independent packet processors (P4) provides a potential possibility for the deployment of Named Data Networking (NDN), which has aroused tremendous attention in academia. Existing P4-based NDN solutions mainly focus on how to describe the stateful forwarding characteristics of NDN in a programmable switch environment. However, the existing solutions still face many challenges such as cache availability and data confidentiality and do not support retransmission of interest packets and multicast forwarding of data packets. In this paper, we propose a new NDN forwarding plane based on programmable switches to address the above challenges. We design a decoupled cache module to avoid a large impact on the data plane forwarding performance when the cache function is enabled. Also, we enhance the design of the existing P4-based NDN forwarding plane to support interest retransmission and multicast forwarding of data packets. In addition, with the advantage of network programmability of P4 technology, we extend the content permutation algorithm and integrate it into the NDN forwarding plane, which makes our scheme support lightweight secure forwarding. Finally, we evaluate our scheme in the prototype system and conduct comparative experiments with representative schemes. Experiment results show that our scheme outperforms it in terms of content retrieval latency and received throughput and can support lightweight secure forwarding with low cost. [ABSTRACT FROM AUTHOR]

The current sustainability challenges and the required systemic transformation highlight the need for innovations on multiple levels. Ecodesign integrates environmental aspects into product and process design to reduce environmental impacts, whereas eco‐innovation also concerns nontechnological solutions. In this paper, we formulate a model that combines eco‐innovation targets ad mechanisms with sustainability maturity, which also concerns stimuli and barriers faced by companies and ecodesign tools used. The results are based on a questionnaire sent to 902 textile and information technology (IT) companies (N = 104) in the Nordic countries. The tools that Nordic textile and IT companies use in particular are life cycle assessment, type I ecolabel, and carbon footprint. Internal stimuli, especially general willingness, were important for eco‐innovativeness, while legislation and customer demand also pushed companies forward. Specific no‐go barriers were not identified, although increase in costs was a common barrier. The respondents focus often on technological product innovations, but rarely on functional innovation, renting of products, and so forth. This highlights the need to address the availability of the right kind of tools to support a broader suite of innovation that can drive toward the circular economy. [ABSTRACT FROM AUTHOR]

This paper models the multi-tier shuttle warehousing system and optimizes the system structure and control strategy. This kind of system is a discrete event dynamic system because it only takes place at discrete time points, while previous warehousing system models. We propose the object-oriented timed colored Petri net to model it, to improve the accuracy of the model and avoid the problem of status explosion in the process of Petri net modeling. We propose two control strategy optimization methods: one is to balance the task assignment, and the other is to change the return time point of the buffer status information. The results of numerical experiments show that consideration of both optimization strategies can reduce the total picking time by 40 % ∼ 62 %. Additionally, we analyze the influence of the buffer capacity. The results show that the buffer capacity can reduce the total picking time, and enough amount of buffer capacity has the same effect as control strategy optimization. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries are an ideal power supplier for electric vehicles (EVs) due to their high-power density and wide operating voltage, but their performance decays to 80% before retirement from EVs. Nevertheless, they still have a particular use value after decommissioning, so recycling the retired power battery in cascade can be considered. Therefore, accurate estimation of battery state-of-charge (SoC) and state-of-health (SoH) is crucial for extending the service life and echelon utilization of power lithium-ion battery packs. This paper proposes a comprehensive co-estimation scheme of battery SoC/SoH for the second-use of lithium-ion power batteries in EVs under different cycles using an adaptive extended Kalman filter (AEKF). First, according to the collected battery test data at different aging cycle levels, the external battery characteristics are analyzed, and then a cycle-dependent equivalent circuit model (cECM) is built up. Next, the parameter estimation of this battery model is performed via a recursive least square (RLS) algorithm. Meanwhile, the variations in internal battery parameters of the cycle numbers are fitted and synthesized. Moreover, validation of the estimated parameters is further carried out. Based on this enhanced battery model, the AEKF algorithm is utilized to fulfill battery SoC/SoH estimation simultaneously. The estimated results of SoC/SoH are obtained for a LiCoO2 cell in the case of CCC (constant current condition) under different cycle times. The results show that this proposed co-estimation scheme can predict battery SoC and SoH well, wherein the peak values of the SoC errors are less than 2.2%, and the peak values of SoH, calculated by the estimated capacity and internal resistance, are less than 1.7% and 2.2%, respectively. Hence, this has important guiding significance for realizing the cascade utilization of lithium-ion power batteries. [ABSTRACT FROM AUTHOR]

The growing popularity and penetration of electric vehicles (EVs) bring in challenges and opportunities to the power grid. They represent a huge aggregate electricity consumption from the city power grid, while it is possible to make use of their batteries for supporting vehicle-to-grid (V2G) regulation service. Besides, there is a need to coordinate a collection of EVs in an intelligent manner through the smart transportation system in a smart city. In this paper, we propose a novel smart cross-system framework to support V2G regulation service in a smart city. Specifically, by considering electric buses (EBs) as a particular group of EVs with large battery packs installed and predictable operation schedules, we jointly solve the problems of EB allocation and scheduling with V2G regulation service. First of all, by using the deep learning approach, the short-term city traffic conditions can be predicted via the gated recurrent units (GRUs) neural network. With the predicted traffic conditions, we then formulate the EB allocation and V2G scheduling as a mixed-integer quadratic programming (MIQP) problem. In order to solve this problem effectively, we utilize the Lagrangian dual decomposition method to decouple the main problem into subproblems for EBs and devise a distributed algorithm to solve each subproblem. The simulation results show that our proposed approach is effective in EB allocation and V2G scheduling for the regulation service. Through efficient EB routing strategies under accurate predicted traffic conditions, the power fluctuations of the city power grid can be well flatten by providing the V2G regulation service. [ABSTRACT FROM AUTHOR]

Several factors like returns, undelivered and damaged goods, exchange, and environmental concern make reverse logistics (RL) inevitable in an E-commerce supply chain. In spite of understanding the importance of RL in current business scenario, most of the companies concentrate on forward logistics, while reverse flow from customer to upstream business is not receiving much interest. Considering this less focused aspect of reverse logistics, the objective of this research is to identify and propose a model to rank the inhibiting variables i.e. the barriers so the logistician can solve them as per the priority. The extensive literature survey and experts' opinion helped in identifying 16 barriers for the study. But the availability of a number of barriers makes evaluating and selecting the most important RL barrier a challenging task and thus it can be dealt with as a multi-criteria decision-making problem. In this paper, a methodology based on analytic hierarchy process has been used to prioritize the barriers of RL. Findings of this paper show that the lack of investment in reverse logistics, lack of understanding about best practices and uncertain return and demand are the three topmost barriers for RL of E-commerce companies. [ABSTRACT FROM AUTHOR]

Copyright of Zeszyty Teoretyczne Rachunkowości is the property of Stowarzyszenie Ksiegowych w Polsce Rada Naukowa and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Cloud computing has invaded our lives so beautifully, that it is time to make cloud more productive. What makes Cloud computing novel is the possibility of an almost immediate resizing of resources on a pay-as-you-go usage model. With companies moving forward with various cloud initiatives, cloud consumers are discouraged from relinquishing their control of the infrastructure to the cloud providers. The rivalry among cloud providers to stay competitive in the market makes it necessary to lock-in its customers, and therefore customers cannot migrate easily to another due to non-interoperable APIs (Application Programming Interface), portability and migration issues. In addition, today's cloud users are mobile devices and consuming a cloud service onto mobile device poses another set of risks. One way to handle this complexity is to devise an intermediary which can take care of the heterogeneity at the cloud and mobile level, and ensure a multi-cloud deployment of application by taking advantage of the best features from different vendors simultaneously. Thus, this paper is a sincere initiative to understand the problem beneath multi-cloud solutions and their embrace for the mobile world. Hence, the following paper begins with a broad coverage of existing work, gives an outline of a multi-cloud middleware, and discusses existing issues with API heterogeneity which is the prime point of concern in the vendor lock-in issue. [ABSTRACT FROM AUTHOR]

Normal log lengths in Norway are 3-6 m (NL), but occasionally there is a demand for short timber with a 2.5 m log length (ST). There are concerns that ST could reduce the forwarders' productivity. Six type stands were created based on harvester data. Different assortment distributions, conditions, and forwarders were simulated in each type stand. It was found that an additional ST assortment almost always decreased productivity (from -15.5 to +4%). Increased forwarding distance (m), more difficult driving conditions, and increased log concentration [m³·(100 m strip road)-1] decreased the productivity difference between sites with ST and NL and sites with only NL. Increased forwarder size increased the productivity difference between sites with ST and NL and sites with only NL. It is possible to load two stacks of ST on some forwarders. Such loading was more productive than loading one stack on longer forwarding distances, while the opposite was the case on short distances. However, loading two stacks of ST can lead to overloading. [ABSTRACT FROM AUTHOR]

Empty containers need to be repositioned from a surplus area to a shortage area, and the resulting economies of scope mean that the canvassing (i.e., the sale of transportation service) of two routes back and forth is no longer isolated. To study the liner company's canvassing strategy for round-trip routes, this paper considers a benchmark situation where one forwarder is responsible for two directions and three canvassing sequences with one direction one freight forwarder responsibility. The results indicate that the liner company should focus canvassing on fewer forwarders, and the forwarder should expand service scope. Under one direction one freight forwarder responsibility, it is not necessarily optimal for the liner company that the direction with low potential market demand canvasses first. Examining the preferences of the liner company and two forwarders in terms of canvassing strategy, we find that a triple-win situation can not be formed, but only a win-win situation can be formed between the two of the three participants. Although the canvassing strategy where the direction with high potential market demand canvasses first has the worst effect on balancing cargo flow, it is possible to increase the market share while improving the profit of the liner company. [ABSTRACT FROM AUTHOR]

The decision problems in the design and control of warehousing order picking process include layout design, storage assignment, routing, and order batching policies. Previous researches on layout design for pick-and-pass systems are not abundant. However, a pick-and-pass system is a commonly used approach because of the growth of e-commerce and the faster delivery of small and frequent orders. This paper presents an algorithm to determine the number of zones, and the number of picking bins and racks in each zones for the pick-and-pass systems such that both investment and operational costs can be minimized. A cycle time evaluation model is developed and incorporated into the proposed algorithm to aid a warehouse designer to quickly evaluate design alternatives for warehouse configurations. The result indicates that the cycle time evaluation model appears to be sufficiently accurate for practical purpose and the optimal layout can be determined by the proposed algorithm. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) has gotten a lot of attention as a next-generation Internet application, and its realization, which connects things, people, and things, is the focal point of a new round of high-tech competition around the world. Network technology has a significant impact on people's lives today, thanks to the rapid development of the Internet, and the Internet of Things (IoT) is a technological innovation of the times that promotes the development of information technology. The Internet of Things has given the logistics industry a new lease on life, allowing it to grow more intelligently. The modern logistics industry is a modern service industry that includes transportation, warehousing, freight forwarding, information, and other industries, and it is very important. This paper examines the technical system of the Internet of Things and the logistics economic management mode, as well as the impact of the Internet of Things on logistics economic management. A multidimensional collaborative management model of environment and economy is proposed, based on the background of IoT. It has laid the groundwork for the IoT's application and development in the logistics economy. [ABSTRACT FROM AUTHOR]

Service oriented enterprise computing is an integration architectural style aimed to expose and consume coarse grained and fine grained modularization of business functionalities as services that are being deployed in the loosely coupled organizational environment. The web service is the implementation technology of service oriented architecture (SOA) where it is built on the existing networking and web interfacing standards as it has to use the web as a medium of communication and does not have any specialized in-built layer for security. The majority of the vendor security products in the market need specialized hardware/software components, eventually, they break the standards and principles of service oriented architecture. The traditional way of problem solving is not effective for developing security solutions for service oriented computing, as its boundaries keep expanding beyond a single organizational environment due to the advent of communication and business technologies such as the Internet of Things (IoT), hyper-personalization, and edge computing. Hence, it is a mandatory entity in this digital age of enterprise computing to have a specialized authentication and authorization solution exclusively for addressing the existing security gaps in SOA in an adaptive way forward approach. In this paper, the security gaps in the existing Identity and Access Management (IDAM) solutions for service oriented enterprise computing are analyzed, and a novel intelligent security engine which is packed with extended authentication and authorization solution model for service consumption is presented. The authentication and authorization security requirements are considered as cross cutting concerns of SOA implementation and the solution is constructed as Aspect-Oriented Programming (AOP) advices, which enables the solution can be attached as a ‘plug & play’ component without changing the underlying source code of the service implementation. For Proof-of-Concept (PoC), the proposed authentication and authorization security model is tested in a large scale service oriented enterprise computing environment and the results have been analyzed statistically. It is evident from the results that the proposed security model addresses security issues comparatively better than existing security solutions. [ABSTRACT FROM AUTHOR]

In this paper, we study the disruptive power of the mobile digital sharing economy to the road freight logistics industry. New information technologies, such as the mobile internet, mobile payment methods, and GPS, have enabled platforms to match freight shippers' demand with carriers' supply by utilizing the convenience and mobility of smartphones. We empirically study the influence of the emergence of mobile digital freight matching platforms in the U.S. on the profitability and stock performance of two types of incumbent road freight logistics companies: freight arrangement companies (freight forwarders and brokers) and trucking companies (freight carriers). Since the mobile digital freight matching platforms mainly match small and mid‐sized trucking companies with shipping demand, we expect the platforms to introduce interference (direct) competition to traditional freight arrangement companies and exploitation (indirect) competition to large trucking companies, which potentially raises operational challenges for both types of incumbents. We use Difference‐in‐Differences (DID) analyses to study the incumbents' profitability and the event study method to evaluate their stock performance. We find that after the advent of the mobile digital freight matching platforms in the U.S., the profitability of the traditional freight arrangement companies counter‐intuitively remained unchanged. In contrast, the profitability of the large trucking companies increased. Furthermore, we examine the changes in sales and costs behind these profitability changes. Our dynamic analyses suggest a time lag of the influence of the mobile digital freight matching platforms. Besides, we find that the stock value of the traditional freight arrangement companies received a significant negative shock, whereas the stock value of the large trucking companies showed no significant reaction. This study contributes to understanding the disruptive power of an emerging technology innovation of sharing economy to firm performances in an increasingly competitive and innovative business environment. [ABSTRACT FROM AUTHOR]

Trade plays an important role in economic growth. Thence, a smooth cross-border transaction between Thailand-Malaysia-Singapore provides a significant implication in international trade. Currently, cross-border transactions face several issues during the crossing of borders between countries and, specifically, happens during the transactions of cargo. A very rigid documentation process within the custom clearance and theresulting severe congestion will affect the trade flow in this particular zone. Inconsistency of freight transaction documents at the cross-border also makes the transaction procedure more complicated and affects the performance of the manufacturer’s competitiveness. Thus, this paper explores the current issues at the borders involving Thailand-Malaysia-Singapore. This paper also initiates to figure out the challenges and some key success factors in modelling efficiency for crossborder transactions amongst these countries. A qualitative approach has been adapted to answer the proposed research questions. The initial results stressed that congestion, thorough and repetitious documentation procedures, involvement of many documents, as well as the time-consuming clearance of documents are key issues encountered during cross-border freight movement. This situation has caused several issues such as delays in freight delivery, losses in tax collection due to delays, reluctance to share information, and effects on the competitiveness of the freight supply chain. Development in infrastructure, information sharing, regulations, logistics performance, and customs clearance procedure can overcome the problems during cross-border Thailand-Malaysia-Singapore activities. The model outcome is expected to be smoother for the administrative process during customs clearance and it is expected to be able to efficiently reduce costs. [ABSTRACT FROM AUTHOR]

This paper focuses on analysing the determinants of satisfaction (service quality, perceived value), as well as its possible influence on customer loyalty of freight forwarders to freight transport service providers (by road/maritime/air) in Spain. To this end, we propose a causal model tested using information from 205 freight forwarders collected through personal interviews. The model was estimated using the Partial Least Squares (PLS) approach. Moreover, the existence of differences in the perceptions on the analysed variables between transport modes is tested through ANOVA. Results show that service quality has an influence on customer satisfaction, both directly, as well as through perceived value. In turn, it is confirmed the relationship between satisfaction with the transportation company and customer loyalty. Furthermore, there are significant differences in quality dimensions and satisfaction between transport modes. This study confirms the importance of service quality and perceived value to promote the link between chain actors: freight forwarder and transport service provider. The main aim of this research is to go deeper into the study of satisfaction and loyalty of freight forwarders to freight transport service providers. Findings provide evidence about differences in the dimensionality of service quality between B2C and B2B settings and, even in the latter, differences between freight forwarding services and other industries are observed. The present paper is one of the few studies that obtains relevant information about several transport modes simultaneously and the findings reinforce the notion that perceptive processes in each of them are different. [ABSTRACT FROM AUTHOR]

Policy-makers face challenges managing the movement of goods while responding to increasingly urgent sustainability problems. Freight policy is fragmented over many regulatory fields, often with ambiguous or contested objectives. Empirical freight transport research can be difficult to translate directly into policy settings, and policy measures often have substantial unintended consequences, especially over long time periods. These foundational challenges can make effective policy implementation difficult. Through a review of the literature, and drawing on diverse applied research and practice experiences, we categorise intertemporal problems in designing regional freight policy, and identify principles for informing practical policy synthesis. These principles provide a framework for decision-makers who formulate policy, and for researchers who critically evaluate it. Adoption and refinement of these principles will improve the translation of research into policy through time, recognising the inherently complex and uncertain nature of planning for the movement of goods. [ABSTRACT FROM AUTHOR]

The sustained and stable growth of China's market economy promotes the continuous improvement of transportation demand and puts forward higher requirements for transportation products. At present, as a new product, high-speed rail freight has played an important role in cold chain logistics and high-value-added transportation, which is of great significance to effectively reduce the pollution caused by road transportation and further promote the sustainable development of economy and logistics industry. In the previous study, we studied the organization optimization method of high-speed rail freight train operation scheme and the compilation method of high-speed rail freight train diagram based on the overall demand of freight transportation but did not consider the influence of different high-speed rail freight transportation products on the organization scheme. Therefore, in order to ensure the sustainable development of high-speed rail freight business, based on the demand of high-speed freight products (the freight product for short in the following text), this paper focuses on the optimization method of high-speed rail freight train organization scheme considering different demands. A two-stage freight demand analysis method considering customers' choice intention and actual supply capacity was designed, comprehensively considering the relationship between operation cost and income, and a model based on different products in order to meet the needs of large-scale case solving was established. In addition, a column generation algorithm was designed. The computational results are encouraging and demonstrate the effectiveness of the model and solution method. [ABSTRACT FROM AUTHOR]

This paper proposes a blockchain-based framework to improve the efficiency of ship traffic in port. In the framework, ship agents, terminals, tug company, pilot station, and government share information and the information is stored in a blockchain. Based on the shared information, we discuss three categories of data-driven models that can improve the operations management of the above five parties. The first category is decisions made by a single party. The second category involves decisions of at least two ship agents. The third category relates to multi-party decision-making under uncertainty. This study hopes to stimulate maritime practitioners to embrace blockchain technology and data-driven approaches to enhance the competitiveness of the industry. [ABSTRACT FROM AUTHOR]

Logistics is a cost sensitive industry with large and fast growing routing networks. In this paper we devise a computational, robust optimization method for the strategic routing decisions of a logistics' customer, i.e., a company that uses the services of different freight forwarders to meet its transportation demands between several sources, sinks, and hubs. The costs of such transports are determined by tariff systems that typically show economies of scale and reward the consolidation of goods that complement each other in properties relevant for transport, such as weight and volume. In the strategic planning phase, routes and hubs have to be chosen roughly one year ahead, in particular, before the actual demand is known. Our method anticipates the fluctuation of demands by minimizing the worst-case cost over a restricted scenario set. The combination of a realistic cost function, a robust modeling of uncertainty, and large-scale networks leads to highly intractable models. We show that the corresponding adversary problem is NP-hard. To nevertheless find solutions for real instances with very good worst-case cost we derive a carefully relaxed and simplified mixed-integer linear program that solves well for large instances because of its powerful linear programming relaxation. We test the method for real-world instances. The results show that robust optimization can significantly reduce worst-case cost. Furthermore, we derive from our method two heuristic techniques to solve even larger networks and report on the corresponding computational results. Neglecting the typical uncertainty about demand values can cause significant cost in logistic routing problems. This paper provides for a practical method to avoid such costs. [ABSTRACT FROM AUTHOR]

Supply chain management is critical for any organization. To improve the performance of a firm's supply chain, it is important to have a freight forwarder evaluation process in place. This paper develops an analytical hierarchy process (AHP) methodology to perform a multi-criteria evaluation of freight forwarders. It analyzes different criteria that would be employed in the evaluation and selection of forwarders. The problem of choosing the best freight forwarder is evaluated in terms of quality of service, specialized service, network, competitive price, information and technology, and sustainability. A total of fourteen sub-criteria are considered including quality of service, network, information and technology, and sustainability. The study revealed that specialized service is the most important criterion with a weight of 54.3% followed by quality of service, competitive price, information and technology, network, and sustainability. Proven experience is the most important sub-criterion with overall weight of 36.2% followed by knowing the regulations with overall weight of 18.1%. Freight forwarder B is the best option with the highest weight with respect to proven experience and knows the regulations with values of 3.62 and 1.629, respectively. [ABSTRACT FROM AUTHOR]

Copyright of SDU Journal of Engineering Sciences & Design / Mühendislik Bilimleri ve Tasarım Dergisi is the property of Journal of Engineering Sciences & Design and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)