Logistics Nodes Research Articles

Investigating into the challenges of European inland ports: A multifaceted approach

Despite their outstanding importance, challenges of inland ports are hardly focused upon in research. Therefore, many major challenges that European inland ports face are neither systematically identified nor addressed. In times of increasing integration of transport chains and modes, inland ports can serve as pivotal enablers in their natural role as intermodal logistics nodes. Hence, addressing the challenges of inland ports supports the efficiency and resilience of entire transport corridors and even logistics networks. With the findings of this research article, the major challenges of European inland ports are identified, systematically collected, empirically validated through semi-structured interviews, and validated with supporting geospatial analyses. On the basis of the findings of this research article, subsequent research can be motivated, initiated, and perpetuated, respectively.

Quality Control of Agricultural Products Cold Chain Logistics under Internet of Things Technology

China's agricultural production has achieved fruitful results in recent years, but on the whole, problems such as scattered production, low degree of modernization and lack of integrated organization and operation of production, supply and marketing are still outstanding. However, the achievement of the synergy benefits of cold chain logistics systems cannot be achieved overnight. Relevant entities should consciously and gradually adopt organized strategies and means to promote the evolution of self-organized collaboration to a higher stage. It is of great practical significance to explore the collaborative path and realization mechanism of cold chain logistics of agricultural products in China under the technology of IOT (Internet of Things), to promote relevant enterprises to solve the "bottleneck" of industrial development in interactive coordination, and to realize seamless connection of cold chain logistics nodes and effective integration of resources. To a certain extent, the wholesale market can more accurately control the types and quantities of products demanded by the market, and also has the ability to schedule all links. Build a backbone network of agricultural products cold chain connecting the main producing areas and consumption areas of agricultural products, and improve the security level of large-scale agricultural products logistics.

ИСПОЛЬЗОВАНИЕ ТЕХНОЛОГИИ ДОПОЛНЕННОЙ РЕАЛЬНОСТИ В ЛОГИСТИЧЕСКОЙ ОТРАСЛИ

The article explores the possibility of using augmented reality technology on the example of enterprises in the logistics industry. As part of the work, the advantages and disadvantages of introducing technology into logistics nodes are evaluated to further improve the work of the entire enterprise as a whole.

A distribution center location optimization model based on minimizing operating costs under uncertain demand with logistics node capacity scalability

Logistics center location optimization is one of the core issues in the study of logistics networks. A sensible logistics center distribution can improve the efficiency of goods transportation and the operation efficiency of logistics enterprises. In this paper, we study the problem of optimizing the location of logistics distribution centers in logistics networks with the objective of minimizing the operating costs of logistics distribution centers. Then, we presents a distribution center location optimization model based on minimizing operating costs under uncertain demand with logistics node capacity scalability. Firstly, the future goods quantity prediction data of each node is obtained through the grey-residual Markov chain prediction model. Then, a logistics center location optimization model with three node expansion mechanisms is developed with the objective of minimizing the objective function. Finally, by using the forecast data of goods demand obtained by the grey-residual Markov chain prediction method, we conducted simulation experiments on the cost-minimizing logistics center location optimization model under three different node expansion methods. The corresponding simulation results are obtained by particle swarm optimization algorithm to prove the effectiveness of the model.

Analysis of Airport Optimal Location in Papua Province as a Support for Logistics Center Distribution Development

Papua is the largest province in Indonesia. It covers an area of 316,552.6 km2. Papua Province consists of 28 regencies and one city, with a population of 4.03 million in 2020. The main mode of transportation as a link between regions in this province is air transportation, in addition to the development of sea transportation through the Sea Toll program and land transportation with the construction of the Trans Papua Road. This study takes the point of view of the transportation network, especially for air transportation, as the mode of choice backbone of the logistics distribution in the Papua area. Considering these conditions, this study considers that the airport is a logistics node, so it is necessary to inventory the number of airports in Papua Province. The method of this study was the shortest path which was included in a network model for determining the shortest and various routes. It analyzed the answers to questions such as which one will be the shortest, fastest, or cheapest route to go to a location and determined locations for logistics facilities, such as distribution centers and warehouses. The study's results were the object of this research is the airport listed on the website. Analysis of the shortest route between airports in the Instrument Flight Rules (IFR) Route Papua area network produced a distance matrix between airports. It resulted four scenarios of the number of airports and their respective service areas.

Design a Robust Logistics Network with an Artificial Physarum Swarm Algorithm

The robust optimization of logistics networks can improve the ability to provide sustainable service and business sustainability after uncertain disruptions. The existing works on the robust design of logistics networks insisted that it is very difficult to build a robust network topology, and this kind of optimization problem is an NP-hard problem that cannot be easily solved. In nature, Physarum often needs to build a robust and efficient topological network to complete the foraging process. Recently, some researchers used Physarum to build a robust transportation network in professional biological laboratories and received a good performance. Inspired by the foraging behavior of natural Physarum, we proposed a novel artificial Physarum swarm system to optimize the logistics network robustness just on a personal computer. In our study, first, the robustness optimization problem of a logistics network is described as a topology optimization model based on graph theory, and four robustness indicators are proposed to build a multi-objective robustness function of logistics network topology, including the relative robustness, the betweenness robustness, the edge robustness and the closeness robustness. Second, an artificial Physarum swarm system is developed to simulate the foraging behavior of a natural Physarum swarm to solve this kind of complex robust optimization problem. The proposed artificial Physarum swarm system can search for optimal solutions by expansion and contraction operations and the exchange of information with each other through a self-learning experience and neighbor-learning experiences. The plasmodium of Physarum forms the edges, and the external food sources simulate the logistics nodes. Third, an experimental example is designed on the basis of Mexico City to verify the proposed method, and the results reveal that the artificial Physarum swarm system can help us effectively improve the logistics network robustness under disruptions and receive a better performance than natural Physarum. The article may be helpful for both theory and practice to explore the robust optimization in logistics operation and provide engineers with an opportunity to resist logistics disruptions and risk loss by a novel artificial intelligence tool.

Carbon emission effects of publicly planned logistics nodes: experience from Chengdu, China.

Both academics and policymakers regard publicly planned logistics nodes (PPLN) as a potential measure to promote logistics agglomeration and mitigate environmental damage caused by logistics activities. However, such measure may lead to non-linear carbon emission effect from the perspective of agglomeration economy, and empirical evidences are yet to be found to verify this inference. This paper uses DID method and mediating effect models to explore the effects and mechanisms of PPLN on CO2 emissions with panel data from 2000 to 2017 in Chengdu, China. Our findings show that PPLN promotes the agglomeration of both small and large-scale logistics enterprises and increases carbon emissions. In addition, the agglomeration of large-scale logistics enterprises can reduce carbon emissions; the opposite is true for smaller ones. Despite the continuous diminishing of the carbon emission increase, the emission-reduction effect has not been achieved through PPLN operations. Based on the results, the study recommends that the government should appropriately determine the location and scale of PPLN, advocate green construction and industrial upgrading, and adopt differentiated regulatory and incentive measures for enterprises. Logistics enterprises can increase their investment in green technologies and strengthen cooperation with their customers.

Exploring the Spatial Heterogeneity and Driving Factors of UAV Logistics Network: Case Study of Hangzhou, China

Urban logistics is an important research topic in human and economic geography; unmanned aerial vehicles (UAVs) are an emerging technology that has huge potential in the field of logistics with the release of control restrictions on low-altitude airspace. The scientific identification of the spatial pattern and impact factors of UAV logistics networks is greatly significant in regards to UAV logistics planning and scheduling. This study considered the urban logistics network of Hangzhou in 2020 as the research topic and used kernel density estimation, a geodetector, and geographic information system (GIS) spatial analysis technology to systematically analyze the spatial patterns and influencing factors at the city and district scales. The study found that a significant spatial pattern was revealed in the UAV logistics network in Hangzhou, and the logistics nodes showed an obvious “core-edge” structure. The urban population, market scale and logistics infrastructure jointly shaped the structure and function of the UAV logistics network, and logistics nodes had a strong coupling relationship with the urban spatial structure. Through interaction detectors, the technical route of urban UAV logistics network construction was analyzed and summarized, and results can provide a scientific basis and case reference for other cities to build and plan UAV logistics networks.

Logistics Optimization Strategy Based on Deep Neural Framework.

We propose a logistics optimization method based on improved graph convolutional networks to address the current problem of low product delivery rate and untimely product delivery during the peak period of e-commerce activities. Our method can learn excellent planning strategies from previous data and can give the best logistics strategy in time during the peak logistics period, which improves the product delivery rate and delivery time of logistics and greatly enhances the return on investment. First, we add a tensor rotation module to the graph convolution layer to better capture the global features of logistics nodes. Then we add inception structures in the temporal convolution layer to build multiscale temporal convolution filters to obtain temporal information of logistics nodes in different time-aware domains and reduce arithmetic power. Finally, we cooperate with e-commerce platforms to adopt logistics data as the experimental database. The experimental results show that our method greatly accelerates the logistics planning speed, improves the product delivery rate, ensures the timely delivery of products, and increases the return on investment.

The Co-evolution of the Regional Logistics Network in the Chengdu\u2013Chongqing Region Based on Node Attraction

With the formation of urban agglomerations, economic zones, and metropolitan areas, the supporting role of the regional logistics industry in economic development is becoming increasingly prominent. It is of great significance to study the spatiotemporal evolution and the coordinated development of regional logistics networks to realize regional integration. In this paper, we propose the weighted co-evolution model of regional logistics networks based on node attraction by introducing concepts such as logistics attractiveness, geographic space distance, and logistics node level, and we integrate the true regional situation into the evolution model. Taking the Chengdu–Chongqing region as an example, we analyze the co-evolution simulation of the area’s regional logistics network. The results show that (1) there are three node connections between new and original nodes, and 50 nodes are added per time interval, which is an ideal situation for studying the evolution of a regional logistics network; (2) the future evolution of the regional logistics network in the Chengdu–Chongqing region can be divided into three stages: the initial construction period from the initial state to the T2 stage, the slow maturity period from T2 to T3, and the coordinated development period from T3 to T4. This research serves as a reference for government managers to formulate logistics development plans.

Research on Intellectualized Location of Coal Gangue Logistics Nodes Based on Particle Swarm Optimization and Quasi-Newton Algorithm

The optimization of an integrated coal gangue system of mining, dressing, and backfilling in deep underground mining is a multi-objective and complex decision-making process, and the factors such as spatial layout, node location, and transportation equipment need to be considered comprehensively. In order to realize the intellectualized location of the nodes for the logistics and transportation system of underground mining and dressing coal and gangue, this paper establishes the model of the logistics and transportation system of underground mining and dressing coal gangue, and analyzes the key factors of the intellectualized location for the logistics and transportation system of coal and gangue, and the objective function of the node transportation model is deduced. The PSO–QNMs algorithm is proposed for the solution of the objective function, which improves the accuracy and stability of the location selection and effectively avoids the shortcomings of the PSO algorithm with its poor local detailed search ability and the quasi-Newton algorithm with its sensitivity to the initial value. Comparison of the particle swarm and PSO–QNMs algorithm outputs for the specific conditions of the New Julong coal mine, as an example, shows that the PSO–QNMs algorithm reduces the complexity of the calculation, increases the calculation efficiency by eight times, saves 42.8% of the cost value, and improves the efficiency of the node selection of mining–dressing–backfilling systems in a complex underground mining environment. The results confirm that the method has high convergence speed and solution accuracy, and provides a fundamental basis for optimizing the underground coal mine logistics system. Based on the research results, a node siting system for an integrated underground mining, dressing, and backfilling system in coal mines (referred to as MSBPS) was developed.

An Optimization Model of Reverse Logistics Network Design

With the increasing development of China’s economy, product and materials of reverse logistics is also increasing. Reverse logistics network design is of great significance to reduce cost of reverse logistics enterprises and society. In this paper, 0-1 mixed integer programming is used to establish a reverse logistics network optimization model which takes into account establishment of fixed facilities and flow between different logistics nodes. The objective function is profit maximization, and the constraints contain the processing capacity of facilities vehicle loading capacity. Lingo 14.0 is used to solve the model. The results show that the application of the model can improve the profits of reverse logistics enterprises on the basis of optimizing logistics facility allocation and material flow.

The study on site selection of fresh food logistics distribution center of large supermarket chains

With the development of fresh food consumption upgrade and the growing consumer demand for high quality fresh food products, traditional fresh food logistics and distribution centers are facing the dual challenges of delivery speed and guaranteeing product freshness. To this end, this paper focuses on the site selection of fresh food logistics center of company Y. First, the fuzzy comprehensive evaluation method is used to screen out suitable alternative logistics nodes and reduce the fixed cost of site selection. Secondly, a mixed integer planning model including freshness index is constructed to reduce the cost of goods loss in the overall distribution process. Finally, the model is solved using Lingo11 to select and confirm the optimal site for the fresh food logistics center.

Design of industrial logistics information integration method based on supply chain management

Considering the problem of traditional information integration error and long processing time, this paper designs an industrial logistics information integration method based on supply chain management. Build the industrial logistics information integration method framework. Due to the diversity of industrial logistics information, use SVM information mining method, and then obtain the affiliation of each logistics node according to the characteristics of the supply chain. In a unified coded environment, nodes with the same attributes are collected and integrated according to the close relationship between different samples to complete the integration of industrial logistics information. Simulation results show that the minimum processing time required by the proposed method is 0.7 min, and integration error is always below 4.8%, effectively reducing the information integration time, reducing interfering the irrelevant information to the integration process and improving the accuracy of the integration results.

Smart Sustainable City Manufacturing and Logistics: A Framework for City Logistics Node 4.0 Operations

The location of smart sustainable city multi-floor manufacturing (CMFM) directly in the residential area of a megapolis reduces the delivery time of goods to consumers, has a favorable effect on urban traffic and the environment, and contributes to the rational use of land resources. An important factor in the transformation of a smart city is the development of CMFM clusters and their city logistics nodes (CLNs); the key elements of the logistics system of a megapolis. The primary goal of this study was to examine the role of the CLN4.0, as a lead sustainability and smart service provider of a CMFM cluster within the Industry 4.0 paradigm, as well as its value in the system of logistics facilities and networks of a megalopolis. This paper presents an innovative model of a CLN4.0 under supply uncertainty using a material flow analysis (MFA) methodology, which allows for specific parameters of throughput capacity within the CMFM cluster and the management of supply chains (SCs) under uncertainty. The model was verified based on a case study (7th scenario) for various frameworks of a multi-floor CLN4.0. The validity of using a group of virtual CLNs4.0 to support the balanced operation of these framework operations under uncertainty, due to an uneven production workload of CMFM clusters, is discussed. The results may be useful for the decision-making and planning processes associated with supply chain management (SCM) within CMFM clusters in a megapolis.

Evolution of Freight Villages and Dry Ports from the Macro Logistics Perspective Based on European Benchmarking 2020

Being the initiator of the German and European Freight Village ranking, Deutsche GVZ-Gesellschaft (DGG) has the methodical know how to create the benchmarking studies. In this ranking approximately 100 Freight Village locations were analysed and evaluated. The research was based on the generation of an uniform understanding, which was focused on intermodality and the significant distinctive management structures. This data led to a qualitative and detailed overview. Because of the positive response, we were motivated to start the second ranking in 2015, as well as the update in 2019/2020. The results of the ranking show important basics and facts, which demonstrate the importance of the Freight Villages and strengthened their role as central, intermodal logistics nodes. Moreover, the responsible decision makers in the Freight Villages benefit from the results of the benchmarking. Many management companies use their placement in the ranking for public relations activities. Good placements or improvements are important instruments in marketing strategies.

An approximation of balanced score in neutrosophic graphs with weak edge weights

Neutrosophic concept is known undirected graph theory to involve with complex logistic networks, not clearly given and unpredictable real life situations, where fuzzy logic malfunctions to model. The transportation objective is to ship all logistic nodes in the network. The logistic network mostly experiences in stable condition, but for some edges found to be volatile. The weight of these erratic edges may vary at random (bridge-lifting/bascule, ad hoc accident on road, traffic condition) In this article, we propose an approximation algorithm for solving minimum spanning tree (MST) of an undirected neutrosophic graphs (UNG), in which the edge weights represent neutrosophic values. The approximation upon the balanced score calculation is introduced for all known configurations in alternative MST. As the result, we further compute decisive threshold value for the weak weights amid minimum cost pre-computation. If the threshold triggers then the proper MST can direct the decision and avoid post-computation. The proposed algorithm is also related to other existing approaches and a numerical analysis is presented.

Conceptual design and assessment of a mars orbital logistics node for sustainable human exploration

Logistics supply chains with nodes at critical locations such as the Earth’s surface, Earth’s orbit, cis-lunar space, Mars orbit and the surface of Mars are crucial to enable sustainable human exploration of Mars. The concept of a Mars orbital logistics node is envisaged to have at least aggregation, refueling, resupply and refurbishing capabilities is defined in this paper. Its elements are analogous to platforms like the International Space Station and Lunar Gateway. The stationing orbit of the logistics node is one of the primary design drivers in determining the associated propellant requirement. We evaluate ΔV requirements across four phases of the mission—interplanetary transfer, capture and departure, deorbit and entry, and launch and orbit transfer. A comprehensive data base of interplanetary trajectories is analyzed. Perturbations due to Mars’ gravity are considered and multiple options for maneuver are considered herein. Three mission scenarios – long stay crewed, short stay crewed and cargo transfer – are evaluated along with three deorbit concepts. A broad range of Low Mars Orbits (LMO) with periods between 0.4 and 0.6 sols and Highly Elliptical Mars Orbits (HEMO) with periods between 2 and 4 sols is found to fall on the trade-off curve of total ΔV and orbital periods across seven synodic periods. Final orbit selection can be made using this data and a desired criteria and mission timeline. For example, HEMO minimizes propellant to access the stationing orbit from interplanetary trajectory whereas LMO minimizes propellant requirement to access the surface from the stationing orbit. HMO is also favorable for short stay and cargo missions.

Reverse Logistics Location Based on Energy Consumption: Modeling and Multi-Objective Optimization Method

The low-carbon economy, as a major trend of global economic development, has been a widespread concern, which is a rare opportunity to realize the transformation of the economic way in China. The realization of a low-carbon economy requires improved resource utilization efficiency and reduced carbon emissions. The reasonable location of logistics nodes is of great significance in the optimization of a logistics network. This study formulates a double objective function optimization model of reverse logistics facility location considering the balance between the functional objectives of the carbon emissions and the benefits. A hybrid multi-objective optimization algorithm that combines a gravitation algorithm and a particle swarm optimization algorithm is proposed to solve this reverse logistics facility location model. The mobile phone recycling logistics network in Jilin Province is applied as the case study to verify the feasibility of the proposed reverse logistics facility location model and solution method. Analysis and discussion are conducted to monitor the robustness of the results. The results prove that this approach provides an effective tool to solve the multi-objective optimization problem of reverse logistics location.

Joint distribution models in fast-moving consumer goods wholesale enterprise: Comparative analysis and a case study

Joint distribution means multiple clients were provided distribution services together by only one third-party logistics company. It is a unified plan and implementation used in distribution centres and a distribution activity implemented by multiple consortia. Many problems in distribution can be solved through the joint use of distribution warehouse, vehicles and reasonable logistics business, so as to optimize the overall logistics node and route arrangement. This paper mainly discusses the model of joint distribution of fast moving consumer goods, proposes three types of the optimization model of joint distribution system with Chaopi as an example. We draw the conclusion that Chaopi Trading Co., Ltd. is a joint distribution system optimization business model. This paper puts forward several basic distribution models and analyzes them in combination with practical applications, which has strong practical significance. Although the development of public distribution in China is not very fast, it is an inevitable trend. Through the efforts and explorations of the governments of various countries, there will be more and more choices of public distribution models.