Logistics Center Research Articles

Managerial aspects spects of digitalization of the transport and logistics ecosystem

A virtual organization is the newest form of business organizations, one of the forms of which are distributed companies with their own production facilities and transport and logistics resources, or using the services of production and logistics centers located on different continents and in different countries, forming project/matrix management structures, attracting specialists from different countries. The article discusses the advantages and risks of managing distributed organizations based on digital technologies. The authors characterize the fields of activity of distributed companies and assess the potential for their expansion. The trend towards digitalization of management processes determines the logic of transformation of the organizational structure model from a traditional hierarchical to an open, flexible one. It is shown that transportation and logistics functions are critically important in ensuring the activities of distributed organizations, within the framework of which the transfer of raw materials, materials in progress, finished products, goods between production centers, sales centers, intermediaries of various kinds, customers and end consumers is realized.The following research methods were used: scientific review, monitoring, situational, retrospective and prospective analysis, as well as critical assessment and formulation of author’s judgments and conclusions on the scientific basis of leading scientists and specialists in the field of economics, management, logistics, operational work management.

Logistics Center Selection and Logistics Network Construction from the Perspective of Urban Geographic Information Fusion.

The last-mile logistics in cities have become an indispensable part of the urban logistics system. This study aims to explore the effective selection of last-mile logistics nodes to enhance the efficiency of logistics distribution, strengthen the image of corporate distribution, further reduce corporate operating costs, and alleviate urban traffic congestion. This paper proposes a clustering-based approach to identify urban logistics nodes from the perspective of geographic information fusion. This method comprehensively considers several key indicators, including the coverage, balance, and urban traffic conditions of logistics distribution. Additionally, we employed a greedy algorithm to identify secondary nodes around primary nodes, thus constructing an effective nodal network. To verify the practicality of this model, we conducted an empirical simulation study using the logistics demand and traffic conditions in the Xianlin District of Nanjing. This research not only identifies the locations of primary and secondary logistics nodes but also provides a new perspective for constructing urban last-mile logistics systems, enriching the academic research related to the construction of logistics nodes. The results of this study are of significant theoretical and practical importance for optimizing urban logistics networks, enhancing logistics efficiency, and promoting the improvement of urban traffic conditions.

Tws-based path planning of multi-AGVs for logistics center auto-sorting

Tws-based path planning of multi-AGVs for logistics center auto-sorting

Urban Complexity and the Dynamic Evolution of Urban Land Functions in Yiwu City: A Micro-Analysis with Multi-Source Big Data

The diversification of business forms leads to functional and spatial complexity in cities. The efficient determination of the complexity of an urban system is the basis for the scientific monitoring of the multi-functional aggregation within cities. Previous studies on the urban spatial structure were limited by the difficulty of collecting micro-data and the high time cost, and they focused on the macro-spatial structure, lacking fine-grained investigations of the micro-spatial structure. Additionally, high-resolution remote sensing images, which mainly rely on the textural characteristics of the spectrum of ground objects, cannot detect the social and economic functions of ground objects. Thus, it is difficult to meet the actual needs of urban planning and management. The purpose of this paper is to automatically identify the spatial heterogeneity and temporal variation of urban land use functions in the context of complex urban systems. The TF-IDF (term frequency–inverse document frequency) algorithm, a machine learning classification algorithm, and other methods are applied to identify the urban functions and distribution characteristics of the main urban area based on the POI (point of interest) data and urban form data. The results show the following: (1) From 2012 to 2022, all types of land use in Yiwu city grew at different rates, with logistics and warehousing space growing the fastest, which is in line with Yiwu’s goal of building a national logistics center for trade and services. (2) The residential area has a spatial structure with a dense central circle and a scattered periphery extending from northeast to southwest and from east to west. (3) The commercial service sector shows clear spatial differentiation between the core and the periphery. The commercial functional areas of Niansanli, Houzhai, and Chengxi, where the number of commercial POIs is relatively small, are located at the intersection of the administrative subdistricts near the city center, indicating that the commercial economic activities of the downtown subdistrict have a certain spillover effect on adjacent subdistricts. (4) The public facilities of each subdistrict are generally located in the core of each subdistrict, which ensures better convenience and accessibility. (5) Industrial land with a large total area that is scattered and mixed with urban residential land gradually tends to be centralized, forming an industrial belt around the city. This study comprehensively considers the aggregation relationship between urban buildings and land use and improves the accuracy of land identification and functional zoning.

Problems and Activation Strategies of Korea’s Smart Logistics Centers in the ESG Management Era

Problems and Activation Strategies of Korea’s Smart Logistics Centers in the ESG Management Era

Optimizing Logistics and Transportation Locations in the China–Pakistan Economic Corridor: A Strategic Risk Assessment

Logistics centers (LCs) have become a critical component of supply chain networks, playing an essential role in the development and implementation of logistics and supply chain management strategies. Recognizing the importance of LCs, Pakistan and China have initiated an extensive plan to establish and expand an LC system as part of the China–Pakistan Economic Corridor (CPEC) initiative. However, the implementation of this plan has faced challenges due to the inadequate prioritization of factors used to identify LCs. This research proposes a structured framework for selecting LC locations, employing a combination of fuzzy logic and the technique for order of preference by similarity to the ideal solution (TOPSIS). These widely used methods address various challenges encountered in location selection. The findings highlight crucial logistics hubs in China and Pakistan, emphasizing factors such as port accessibility, freight demand, and transportation costs. The prioritization of criteria for LC selection is determined through the evaluation of variables and alternatives. The proposed framework enhances decision-making based on multiple criteria by addressing uncertainty and subjective assessments.

Enhancing Smart Cities through Third-Party Logistics: Predicting Delivery Intensity

This article addresses the key and current issues of smart cities in the context of last-mile supply management. Specifically, it explores how third-party logistics (3PL) activities impact last-mile delivery management in smart cities. It examines how 3PL affects delivery volumes, expanding the predictive capabilities of logistics operators. A research question included in the Introduction of this paper is also posed to explore the problem in depth. The research conducted focuses mainly on a case study conducted on the operations of an international 3PL logistics operator. In addition, predictive methods are used to analyse the shipment volume data for individual barcodes in the two analysed cities in Poland. Currently, the concept of a smart city assumes the limited participation of logistics operators in creating improvements for cities. The case study analysis shows that in the cities studied, 3PL companies, through predictive actions, can regulate the flow of vehicles out of the logistics centre and into the city, thus influencing the traffic volume in the city. The research is limited to two cities in Poland implementing smart city solutions and one logistics operator. The research also does not include e-commerce. The authors acknowledge that the results obtained cannot be generalised to a larger scale. This paper bridges the research gap on 3PL activities for last-mile logistics improvements. In addition, the paper proposes the first concept related to the implementation of a 3PL company’s predictive activities associated with the operator’s ability to control the impact on urban traffic.

Research on Optimization of Agricultural Products Cold Chain Logistics Distribution System Based on Low Carbon Perspective

Based on thindiscussion of the traditional agricultural product distribution model, this article establishes a low-carbon perspective of urban agricultural product co-distribution model to reduce the level of agricultural product circulation and reduce the impact of distribution activities on the environment. By comprehensively considering the factors affecting carbon emissions in the vehicle delivery process, the fuel consumption and carbon emissions estimation models of delivery vehicles are analyzed and put forward. A mathematical model for the optimization of urban agricultural product cold chain distribution routes from a low-carbon perspective is established. This article takes a logistics center as an example, selects genetic algorithm as the model solution method, optimizes the distribution route, and obtains the corresponding result, thus verifying the rationality and feasibility of the model.

Improving the picking efficiency of a cold warehouse to avoid temperature abuse

PurposeThis research investigates how to optimize storage location assignment to decrease the order picking time and the waiting time of orders in the staging area of low-temperature logistics centers, with the goal of reducing food loss caused by temperature abuse.Design/methodology/approachThe authors applied ABC clustering to the products in a simulated database of historical orders modeled after the actual order pattern of a large cold logistics company; then, the authors mined the association rules and calculated the sales volume correlation indices of the ordered products. Finally, the authors generated three different simulated order databases to compare order picking time and waiting time of orders in the staging area under eight different storage location assignment strategies.FindingsAll the eight proposed storage location assignment strategies significantly improve the order picking time (by up to 8%) and the waiting time of orders in the staging area (by up to 22%) compared with random placement.Research limitations/implicationsThe results of this research are based on a case study and simulated data, which implies that, if the best performing strategies are applied to different environments, the extent of the improvements may vary. Additionally, the authors only considered specific settings in terms of order picker routing, zoning and batching: other settings may lead to different results.Practical implicationsA storage location assignment strategy that adopts dispersion and takes into consideration ABC clustering and shipping frequency provides the best performance in minimizing order picker's travel distance, order picking time, and waiting time of orders in the staging area. Other strategies may be a better fit if the company's objectives differ.Originality/valuePrevious research on optimal storage location assignment rarely considered item association rules based on sales volume correlation. This study combines such rules with several storage planning strategies, ABC clustering, and two warehouse layouts; then, it evaluates their performance compared to the random placement, to find which one minimizes the order picking time and the order waiting time in the staging area, with a 30-min time limit to preserve the integrity of the cold chain. Order picking under these conditions was rarely studied before, because they may be irrelevant when dealing with temperature-insensitive items but become critical in cold warehouses to prevent temperature abuse.

Evaluating the Efficiencies of Logistics Centers with Fuzzy Logic: The Case of Turkey

The primary actor in today’s economic life, forming the backbone of the production-consumption cycle, is the distribution activities. Logistics centers (LCs) are organized areas where these activities are carried out together. Therefore, the efficiency and effectiveness of distribution activities are crucial for sustainability. This study incorporates fuzzy logic theory into the framework of data envelopment analysis (DEA) to measure the efficiency of LCs. Classical DEA assumes input and output data are precisely measured, making the efficiency scores unreliable and inconsistent when data precision is not always possible. The adoption of fuzzy logic is primarily to overcome possible uncertainties, errors, and ambiguities in data acquisition, preventing incorrect results. Hence, an approach assumes the data lie within specific intervals, was adopted to calculate the efficiencies of LCs based on α-cut levels. Officially obtained data on nine input and one output variable from twelve LCs operating in Turkey were used to calculate efficiency scores. As a result of the study, Köseköy/Izmit, Halkali/Istanbul, and Yenice/Mersin LCs were found to be fully efficient considering both lower and upper bound efficiencies. Moreover, the efficiency calculations using Fuzzy-DEA allowed for a more precise evaluation of LCs with high data sensitivity.

Көліктік-логистикалық орталықтар менеджментінің оңтайлы құрылымының бизнес моделі

Transport logistics are transport enterprises that are participants in the process of distributing goods, aimed at obtaining a single economic result in the logistics chain. This article discusses the main factors of the company's productivity growth and the priority allocation system. The expansion of transport and logistics systems through the construction and modernization of transport and logistics centers at major transport hubs, mainly in regional centers, is also being considered. The expediency of the applied projects is proved using regression analysis based on the classical modeling method. Optimal management of the management of transport and logistics centers has a number of advantages over the traditional management method, and is also carried out by balancing the requirements of the main groups. The management model in the management of a transport and logistics center is based on five special management processes. In general, this analysis is a classical basic probability method, i.e. fully examines the economic indicators of the enterprise. The model is based on five special management processes. When studying the activities of the supply chain, a single plan provides for the intersection of the processes of supply of raw materials, product preparation, delivery and return, according to which the activities of all partner companies of the chain are coordinated. Companies need to have a good understanding of their place in the supply chain and the possibilities for improving work efficiency.

Eco-green transport and logistics terminal with the suspended cable car

The volume of cargo turnover increases annually, while new large companies appear on the market, which, unlike transport companies, can boast of having their own transport and logistics centers, which gives independence and the opportunity for independent improvement. But at the same time, a sharp increase in the number of vehicles and low road capacity leads to delays in deliveries, which is especially important when transporting food and other goods with a limited shelf life. The situation is aggravated by the workload of logistics centers, the presence of toll booths and crossings on transportation routes, as well as increased taxes and fuel costs. All this is reflected in the added value and competitiveness of the company as a whole. Meanwhile, all these factors have a negative impact on the environment, the amount of waste and harmful emissions increases, which should not be left without due attention. Therefore, at the moment there are prerequisites for a wider use of rope transport for the transportation of goods, namely for the transportation of consumer goods at the level of transport and logistics centers. In the course of the study, the main conditions of application and possible ways of combined use of rope transport were determined. As a result, a mathematical model of the feasibility study was obtained and the optimization function of the transport and logistics terminal with the use of an overhead cable car was determined according to the criterion of total unitcosts.

Modelling Dynamic Traffic Loads in Multiserver Queues using G/G/k Queue

Operations research and marketing management have benefited greatly from the important science of queuing optimisation. We take into account a multiserver single input G/G/k queue for study. This type of queue formation occurs in factories, production facilities, logistics centres, airports, and hospitals where the inter-arrival and service times are frequently not exponentially distributed. Knowing the precise number of service providers needed to avoid congestion at the lowest possible cost would therefore be the main concern. When there are more jobs than servers in a G/G/k queue, the cost incurred by the number of jobs per unit time becomes complex, making it challenging to determine the average cost. As a result, this paper obtains the bound for the ideal number of servers that would reduce the overall cost. Interpolation technique is used to determine the precise number of servers. When there are more servers (k) than job arrivals, the G/G/k queue’s optimal cost per unit time during an execution cycle is obtained. The proposed system is made up of a G/G/k queue that begins operating as soon as the first job enters the system. Due to the general distribution of job arrivals, the time interval between subsequent job arrivals is not always the same. Therefore, the study of an arrival that causes a state transition in the system is taken into account. When there are fewer servers available than job arrivals, an expression is derived to determine the optimal server count. When the number of available servers exceeds the number of jobs in the system, the optimal number of jobs that minimises the average processing cost per unit time for one job is also determined. The simulation results are obtained by simulating this system with MATLAB’s SimEvents toolbox.

The Urban-Rural Interface: Recent Concepts and Changes. The Case of Buenos Aires

Abstract As the city advances on its hinterland, new concepts emerge to highlight the urban-rural relations that take place in the areas where the urban and the rural systems are articulated. This paper takes up different concepts and their characteristics as well as a comprehensive individualization of the Buenos Aires urban-rural interface (UR-I). The paper aims to characterize the UR-I of Buenos Aires through a qualitative methodology. The paper analyses some preliminary discussions that allow us to establish the emergence of new logics of localization and shaping of the industries and logistics centres, large leisure and consumption facilities and the new ways of living, as well as the issue of the productive Buenos Aires UR- I, and invites us to review the territorial processes, the actors and the underlying factors in Buenos Aires.

Aptenodytes forsteri optimization algorithm for low-carbon logistics network under demand uncertainty.

As China's "double carbon" goal continues to advance, logistics as a key area of carbon emissions and low-carbon logistics center site selection are key links in the process. However, existing studies on logistics center location often ignore the impact of demand uncertainty, which leads to a waste of resources in the planning and construction processes. We take logistics cost and carbon emission as the objectives, and the multi-objective site selection model established based on stochastic programming theory takes demand uncertainty as a stochastic constraint. We transform the stochastic constraint model into a 0-1 mixed integer multi-objective planning model by utilizing the idea of equivalence transformation. The Aptenodytes Forsteri Optimization (AFO) algorithm is combined with the Ideal Point Method to solve the model, and the algorithm is compared with the Particle Swarm Optimization (PSO), Differential Evolutionary (DE), Tabu Search (TS), Sparrow Search (SS) algorithms, and the exact solver Linear Interactive and General Optimizer (LINGO). The examples verify the validity of the models and algorithms, with an average reduction of 6.2% and 3.6% in logistics costs and carbon emissions in the case of demand determination, and at the confidence level of 0.9 under demand uncertainty, both logistics costs and carbon emissions are decreased to varying degrees. This study provides a new research idea for the low-carbon logistics location problem under demand uncertainty, which helps to promote the transformation of the logistics industry to low-carbon and high-efficiency.

Simulation and Optimization System of Automated E-Commerce Logistics Warehouse Allocation Network Based on Intelligent Algorithm

The prosperity of e-commerce has made our lives more convenient, but the logistics behind it has been silently paying. The e-commerce industry is expanding at an unprecedented rate, and with it comes explosive growth in logistics demand, especially in the warehouse distribution link. In order to meet this demand, the warehouse distribution system needs to be improved both in terms of technology and efficiency. This rapid development also brings a series of problems. First of all is the problem of logistics congestion. Due to the surge in orders, especially during peak shopping periods, logistics centers are often under great pressure. This not only affects the speed of delivery, but can also lead to damage or loss of goods. The purpose of this paper is to find an effective method to optimize the logistics warehouse allocation system of e-commerce, and to provide an efficient and reliable logistics optimization scheme for e-commerce enterprises. In this paper, data analysis and simulation methods are used to analyze. The experimental results show that PSO has the largest improvement in the order clerk operation efficiency (13%) and the smallest improvement in the order status (1%).

ОЦІНКА ВЗАЄМОВПЛИВУ МАКРОЕКОНОМІЧНИХ ЧИННИКІВ ТА ЛАНЦЮГІВ ПОСТАЧАНЬ В УМОВАХ ВІЙНИ

The article analyzes the main macroeconomic indicators of the national economy: gross domestic product (GDP) in nominal and real terms, GDP per capita, and consumer price index. Their dynamics in the period before and during the full-scale war is studied. It is noted that the gaps in the volumes of real and nominal gross product are explained by the presence of a significant percentage of the shadow economy and inflationary processes in Ukraine. The shadow economy makes it impossible to accurately estimate real GDP, as it does not take into account the informal economy and goods and services that do not pass through supply chains. The paper identifies aspects of the interaction between macroeconomic factors and supply chains. Particular attention is paid to the cause-and-effect relationship between inflationary processes and supply chains. In particular, the following are considered: shocks to the economy due to the lockdown caused by the Covid19 pandemic; full-scale Russian invasion; destruction and relocation of production facilities; disruption of logistics and supply chains; growth in production costs of business entities; migration processes. The article analyzes the dynamics of the consumer price index in Ukraine and European countries in recent years. Russia's full-scale invasion of Ukraine has created a number of new global economic challenges. This has increased costs in the supply chain and affected the supply of goods and, consequently, their prices. Consumer price indices in European countries have risen to their highest levels in recent years. The main ways to optimize the movement of material flows in supply chains in the context of the war in Ukraine at the national and global levels are considered. At the global level, logistics restructuring based on supply chain management concepts has been introduced, humanitarian cargoes have been transported without carriers having to cross borders, logistics centers have been organized for efficient transportation management, and nishoring, onshoring, and friendshoring have been implemented. At the national level, the company has established cooperation with state authorities to find optimal solutions for cargo transportation, and companies use dual-sourcing approaches with the use of digital logistics tools, development of new logistics routes.

考虑不同投资模式的城市群绿色物流中心选址模型

考虑不同投资模式的城市群绿色物流中心选址模型

Research on benefit allocation based on multi-weight H-Shapley value: A case study of express logistics sharing.

Urban last-mile express delivery in China encounters several challenges. This paper presents the establishment of a sharing logistics center aimed at enhancing the overall efficiency of urban last-mile express delivery while optimizing the utilization of essential resources. The successful implementation of shared delivery within sharing logistics center necessitates the creation of a robust collaborative mechanism. Recognizing that cooperative benefit allocation is dynamically influenced by factors such as resource input, operational efficiency, risk management, and other cost-related considerations, this study introduces a multi-weight H-Shapley value method for benefit allocation. By conducting empirical analyses of urban last-mile express delivery in Beijing within a sharing logistics service framework, our findings reveal that the revised benefit allocation model better aligns with the interests of participating entities and positively correlates with their contributions. Analyzing the impact of delivery volume and express operational costs changes, it is found that when the delivery volume and express operational costs of the sharing logistics center change, the benefits of participating enterprises move in the same direction. The benefit allocation model established in this study enriches the existing body of research in the field of shared delivery and offers valuable insights for benefit allocation issues that necessitate consideration of the dynamic effects of multiple parameter variations.

Теоретичні засади розвитку суб’єкта підприємництва в умовах невизначеності

The development of entrepreneurship is considered as a component of social development, which is carried out in three directions: evolutionary, involutional, and abrupt acceleration. The necessity of forming a policy of development of entrepreneurship in Ukraine is indicated and its main tasks are allocated, namely: increasing the volume of production and export of products of Ukrainian enterprises, the formation of new enterprises, ensuring the proper level of satisfaction of domestic demand with goods and services; demonopolization of markets for goods and services and establishment of effective competition in the domestic market; increase and diversification of employment; achievement of an effective fiscal return on business development while maintaining favorable conditions for its development. The general goals of entrepreneurship management include the process of forming a strategy for activity and development and adaptation of business processes of enterprise. It is noted that decision-making by entrepreneurs in conditions of uncertainty should be based on the study of its theoretical foundations, where it is considered in several types: when the results of activities are known and it is possible to predict them; when the results are known, but the probability of them cannot be estimated; when the results are not known and it is not possible to estimate the probability of their occurrence. For the purpose of effective management of the business structure, it is expedient to classify uncertainty by the following types: by methods of determining the probability of occurrence of cases and by the object of uncertainty. Among the main tasks of entrepreneurship management, reducing the likelihood of adverse events and avoiding negative consequences and risks, including strategic ones, are allocated, since the development and implementation of strategic management decisions are the basis for ensuring sustainable development of entrepreneurial entities. It is noted that changes in the institutional environment have an impact on the dynamics of uncertainty. In order to improve business conditions, informal and formal institutions must be aligned, which is a transformation of uncertainty. Directions for the development of entrepreneurial structures have been identified, which should coordinate their actions with the State structures to form an institutional environment. Among such areas, the following are highlighted: creation of commodity exchanges and wholesale markets for products of local producers; formation of market infrastructure of scientific and innovative activities; orientation of commercial banks to the real sector; creation of consulting and leasing firms; development of the stock market, including the formation of the corporate securities market; formation of logistics centers.