Logistics Center Research Articles

Optimisation problem of China’s supply chain transportation issues in European logistics

The paper highlights the importance and validity of the research problem: the major consequence for logistics arising from China’s logistics market due to its effective short-term and long-term strategies and developing transportation wholesale. The presented viewpoint helps to clearly understand the international perspective of the vastly enlarging China’s supply chain market due to its strong links with logistics centres. In recent years, much scientific research and studies have been conducted in China and Europe regarding China’s transport evolution era, from the production stage to the physical distribution stage, involving multiple steps until loads are in customers’ hands. The article considers the optimisation problem of a supply chain with multiple periods and diverse means of transportation. The considered problem can be formulated as a dynamic multi-criteria decision-making problem, in which the criteria are minimising the total cost, minimising the carbon footprint, and minimising the average transporting time.

Sustainable Logistics: Synergizing Passive Design and PV–Battery Systems for Carbon Footprint Reduction

As more companies strive for net-zero emissions, mitigating indirect greenhouse gas emissions embedded in value chains—especially in logistics activities—has become a critical priority. In the European logistics sector, sustainability and energy efficiency are receiving growing attention, given the sector’s intersectional role in both transportation and construction. This transition toward low-carbon logistics design not only reduces carbon emissions but also yields financial benefits, including operational cost savings and new market opportunities. This study examines the impact of passive design strategies and low-carbon technologies in a Swedish logistics center, assessed using the low-carbon design criteria from the BREEAM International standard, version 6. The findings show that passive energy-efficient measures, such as the installation of 47 skylights for natural daylighting, reduced light power density in accordance with AHSHARE 90.1-2019 and the integration of free night flushing, contribute to a 23% reduction in total energy consumption. In addition, the integration of 600 PV panels and 480 batteries with a capacity of 268 ampere-hours and 13.5 kWh storage, operating at 50 volts, delivers a further 56% reduction in carbon emissions. By optimizing the interaction between passive design and active low-carbon technologies, this research presents a comprehensive feasibility analysis that promotes sustainable logistics practices while ensuring a future-proof, low-carbon operational model.

Enabling efficient patient discharge with a mindset, toolset, and skillset framework.

33 Background: Timely access to care for patients coming through the emergency center can be achieved by efficiently discharging patients. When continued bed growth is not sustainable, improvements in team-based approaches to discharges are necessary and require a multi-pronged approach. Our institution embarked on a process improvement effort anchored on completing 1 out of 2 patients discharged by 12PM. We hypothesize that a discharge before noon will assist with getting our next patient to a bed by 2PM. We conducted a pilot on our Stem Cell Transplant units to test and enable our case for change allowing for scale and spread to other units. Methods: Our multi-pronged framework was focused on mindset, toolset, and skillset. As our first step, executive leadership set direction to achieve a shift in mindset by socializing the case for change using a hospital throughput framework including a 9-12-2 branding. A discharge launchpad [toolset] was established to define expectations of discharge tasks including accountability within a 2-day window of medical readiness for discharge. This served as the tool aligning various teams to a date for task completion. Lastly, we evaluated skillset and defined best practices for the unit RN role and APP, along with others, which included empowering various roles to discharge patients. Results: For discharges during the baseline period of 12/1/2022 - 11/30/2023 from the Stem Cell Transplant service, the percent of discharge orders in by 9AM was 10.3% and discharges completed by 12PM was 12.2%. The pilot period month of April 2024 resulted in a month close performance of 52.5% for orders in by 9AM and 55.4% of patients discharged by 12PM. The average time spent by Stem Cell patients boarding in our emergency center during the baseline period was 6 hours and 34 minutes with a reduction to 2 hours and 23 minutes in April 2024. There were no Stem Cell beds added during the pilot period compared to baseline. The period of 12/1/2023 – 3/31/2024 was excluded to limit any improving data from the Hawthorne effect since throughput socialization began during those months. Conclusions: We met the goal within one month with plans underway to assess sustainability for implementation readiness for scale and spread to other units. Early efforts made to scale this model within the institution confirm the multi-pronged model approach is necessary. Additionally, we believe that a frontline leadership model would contribute best to implementation success. Missing any component of the multi-pronged approach or team member, such as the APP role without the RN role, will not yield the ultimate result of discharging patients by noon. This change requires a coordinated, team-based approach. The new institutional governance structure for hospital throughput, including academic and operational departments, and a logistics center in the future may contribute to building trust in leadership’s commitment to improving patient care.

Location selection for logistics centre using PROMETHEE method

Logistics and distribution centres are essential to the supply chains of many manufacturing and logistics companies. Efficiently locating logistic centres involves thorough search for optimal place, prioritizing proximity to suppliers and minimizing costs. Companies’ management often solves the location problem of new halls, mostly to minimise the associated costs. Such a problem is solved in the automotive industry as part of the launch of a new international project. The key factor for the decision of where to locate the logistics centre is the location of the suppliers, since material deliveries generate a large part of the project costs. The aim of this study is to define a methodology for the location of the logistics centre, considering several alternative locations and relevant criteria. The location alternatives and criteria are defined in terms of minimising project costs and sustainability elements. The problem is solved using the multi-criteria decision-making approach. First, the AHP method is used to assign weights to the criteria. Then the PROMETHEE method is applied to find a suitable location for the logistics centre and to perform a thorough sensitivity analysis. The sensitivity analysis is focused on the impact of values of weights on the solution. Consequently, the analysis proves the correctness of the selected alternative. Based on the case study, a general methodology for locating a logistics centre is proposed.

Forecasting material flows of modern logistics centres of railway freight stations exemplifi ed by Xi’an (the People’s Republic of China)

The purpose of the study is to create a more accurate material fl ow forecasting model of Xi’an freight railway station in China. The combined forecasting model is more validated for forecasting freight flows of regional logistics compared to three methods: grey forecasting, Markov chains, entropy weighting. Through the creation of the combined model, the grey forecasting method is combined with Markov chain correction, and the projected data is compared with the actual data to obtain higher accuracy of the forecasting model. A combined model using the grey forecasting method combined with Markov chain correction is created, with the forecast data compared with the actual data to obtain high accuracy of the forecasting model. The practical significance is that in the context of the present post-pandemic economic development, the logistics enterprises that do not operate in accordance with the modern logistics methods may be displaced by competitors. If the railway does not improve its logistics infrastructure, logistics equipment, railway logistics network platform, etc., it will lose out to other modes of transport. In order to meet the needs of logistics and improve the market competitiveness, the main indicator of a freight station is loading and logistics flow. Therefore, exact prediction of future changes in the logistics flow of a freight station can help to determine whether the station needs to be upgraded as a railway station or transformed into a certain type of a logistics centre.

Lead Battery Reverse Logistics Center Location Model and Simulation Analysis Based on Genetic Algorithm and Greedy Algorithm

Lead Battery Reverse Logistics Center Location Model and Simulation Analysis Based on Genetic Algorithm and Greedy Algorithm

An artificial bee colony optimization algorithms for solving fuzzy capacitated logistic distribution center problem

This paper presents a methodological approach to solving the fuzzy capacitated logistic distribution center problem, with a focus on the optimal selection of distribution centers to meet the demands of multiple plants. The distribution centers are characterized by fixed costs and capacities, while plant demands are modeled using fuzzy triangular membership functions. The problem is mathematically formulated by converting fuzzy demands into crisp values, providing a structured framework for addressing uncertainty in logistic planning. To support future research and facilitate comparative analysis, 20 benchmark problems were generated, filling a gap in the existing literature. Three distinct artificial bee colony algorithm variants were hybridized with a heuristic: one using the best solution per iteration, another incorporating chaotic mapping and adaptive procedures, and the third employing convergence and diversity archives. An experimental design based on Taguchi's orthogonal arrays was employed for optimizing the algorithm parameters, ensuring systematic exploration of the solution space. The developed methods offer a comprehensive toolkit for addressing complex, uncertain demands in logistic distribution, with code provided for reproducibility.Key contributions include:•Development of a fuzzy model for the selection of distribution centers with fixed costs and capacities under uncertain plant demands.•Generation of 20 benchmark problems to advance research in the fuzzy capacitated logistic distribution center problem domain.•Integration of a heuristic approach with three distinct ABC algorithm variants, each contributing unique methodological insights.

Expanding the Areas of Attraction of Solutions to Singularly Perturbed Equations

The article analyzes the state and development prospects of the transport and logistics system of automobile transport in the Kyrgyz Republic. The authors consider the key features of the functioning of the automobile sector in the context of the country’s transition economy. The work assesses the current state of automobile transportation of goods and passengers, examines the main problems hindering the increase in the efficiency of the transport and logistics system. These include low technical equipment of the vehicle fleet, insufficient development of the logistics infrastructure, imperfection of legal regulation, personnel shortage. The authors propose a set of measures aimed at modernizing and optimizing the functioning of automobile transport in Kyrgyzstan. Among the key areas are the renewal of the vehicle fleet, the development of a network of logistics centers and multimodal transportation, the introduction of information technologies in transportation management, and the improvement of state regulation of the industry. According to the authors, the implementation of the proposed measures will contribute to increasing the competitiveness and customer focus of automobile transport in the Kyrgyz Republic, which in turn will have a positive impact on the development of the national economy.

Research of the Application of Cargo Volume Forecasting and Simulated Annealing Scheduling Optimization Based on Multi-model Integration in Logistics Centers

Research of the Application of Cargo Volume Forecasting and Simulated Annealing Scheduling Optimization Based on Multi-model Integration in Logistics Centers

Research on Location Optimization of Logistics Center Based on Center of Gravity Method: A Case Study of Jilin Province

With the rapid development of the global economy, logistics plays an increasingly important role in modern society. As the core node of the logistics system, logistics center is responsible for the distribution, transfer and distribution of goods. The scientific and rational location of the logistics center will directly affect the efficiency and cost of logistics transportation. In this paper, Jilin Province, a key agricultural producing area in China, is selected as the research object. By collecting certain historical data information, regression analysis method and moving average method are used to predict the grain output of each city, and the average value of the predicted values obtained by the two methods is used as the final forecast value. The initial site selection of grain logistics center in Jilin Province is calculated by using the center of gravity, and the new site selection after iteration is obtained by using the center of gravity. Finally, the location of the final grain logistics center is determined by considering the factors such as geographical location, traffic accessibility and usable area around. This study can provide some reference value for the optimization of logistics center location.

A Proposed Method and Case Study of Waste Heat Recovery in an Industrial Application

Abstract Waste heat recovered from a refrigeration machine is associated with the double benefit of generating cold and heat with just one unit. Additional energy is required in most cases to achieve these benefits. To evaluate the efficiency of waste heat recovery, two novel efficiency indicators are described. The overhead coefficient of performance (OCOP) describes additional electrical power required to raise the temperature to make waste heat usable. The coefficient of savings describes power reduction when condenser heat is fed into a cold district heating network instead of exhausting it to high-temperature outside air. Results are reported from a case study in a food logistic center with high cooling demand in Isny, Germany. Waste heat at this facility was previously released unused to outside air. We describe how this waste heat can be used to supply sustainable heat supply to a new residential area. During the design phase, it is difficult to choose the best operating temperature for district heating networks (DHNs). The novel indicators are used to value the effort to make waste heat usable. Whereas a supply temperature of 20 °C has no disadvantages for the operator, a supply temperature of 40 °C is associated with an increase in electricity consumption. The resulting OCOPs are above 5.0 even under unfavorable conditions and exceed the theoretically calculated (Holm and Pehnt, 2023, Wärmeschutz und Wärmepumpe-Warum Beides Zusammengehört, Forschungsinstitut für Wärmeschutz e.V., Institut für Energie und Umweltforschung, München/Berlin/Heidelberg, p, 13, 14; Agora Energiewende, Fraunhofer IEG, 2023, Roll-out von Großwärmepumpen in Deutschland, Strategien für den Markthochlauf in Wärmenetzen und Industrie, Berlin) and measured (Fraunhofer Institut für Solare Energiesysteme, 2020, “Wärmepumpen in Bestandsgebäuden, Ergebnisse aus dem Forschungsprojekt, WP-Smart im Bestand.”) coefficients of performance (COPs) for air-sourced heat pumps. Although using waste heat is not free, it is beneficial when overall efficiency is considered.

Determine the Modern Requirements for Architectural Design, depending on the Logistic Center

Determine the Modern Requirements for Architectural Design, depending on the Logistic Center

Characterizing last-mile freight transportation using mobile phone data: The case of Santiago, Chile

Understanding the mobility of surface freight transportation is relevant in urban planning and for developing public policies. Literature shows that most previous efforts on this topic rely on surveys and limited data. In contrast to other works, in this paper, we present an innovative methodology for characterizing last-mile freight transportation that uses a novel and copious data source: mobile phone data, which provides a broader scope. Our methodology involves calibrating supervised machine-learning models that allow us to link cell phones with truck drivers. In this endeavor, we construct several input variables that track mobile phone’s daily movement patterns, including traveled distances, interactions with highway networks, and land use variables. We test our approach by conducting a case study in Santiago, Chile, for which we analyze mobility patterns and logistics indicators disaggregated by day, hour, and zoning. For this case, we show that all supervised models performed well regarding AUC, which can be attributed to the high granularity and handling of the data. However, we chose to use NGBoost in all subsequent experiments, as it provided slightly better results on our validation data. Our work has several implications for practice. For instance, our results can support decision-makers and policymakers in identifying critical areas where urban logistics centers and transportation interventions are needed. Finally, several research lines stem from our work, which include assessing the impact of incorporating geospatial information and the measurement of logistics sprawl over time.

수도권 지역에서 물류센터의 임차 결정 요인에 관한 연구

Purpose: T his s tudy a nalyzed t he f actors i nfluencing t he s election o f logistics c enters for leasing and their impacts on the performance of a firm in metropolitan areas. Understanding these determinants is crucial for efficient logistics management, given the growing importance of logistics centers because of the expansion of e-commerce and delivery services. Research design, data, and methodology: This research was conducted using a structured approach that included a theoretical review, hypothesis formulation, and empirical verification. Data were collected through a survey targeting logistics and distribution experts, and the hypotheses were tested using mediation effect analysis. Results: The geographic location, logistics facilities, architectural features, and external environmental factors significantly impact leasing decisions. These factors also have significant effects on strategic and operational decision-making as well as corporate performance. Conclusions: The choice of logistics centers significantly affects strategic and operational decision-making levels and the management performance of a company. The implications of this analysis suggest that shippers should conduct a detailed and thorough analysis and review when making leasing decisions for logistics centers.

AHP를 활용한 컨테이너 보관창고 입지 결정 중요도 분석

The purpose of this study is to investigate the relative importance of determining factors of location decision regarding container storage warehouses, and thus, provide a method to resolve difficulties when selecting the location of small-sized container storage warehouses by verifying essential factors to consider in location decision. Few studies have examined container storage warehouses, hence, this study attempted to study the difference of location decision between logistics centers and container storage warehouses through Analytic Hierarchy Process (AHP). Results showed that considering the conditions of the hinterland is the most important factor in location decision, followed by traffic accessibility, site conditions, operating entities, and ownership entities. In detail, the most important factor regarding the conditions of the hinterland was whether or not the area had few civil complaints; the most important factor for traffic accessibility was the proximity of infrastructure to the logistics industry; the most important factor regarding site conditions was land price competitiveness; the most important factor in operating entities was whether or not they were self-operated; and the most important factor regarding ownership entities was ownership type.

Emergency logistics siting-path question for engineering construction projects based on quantum particle swarm algorithm

Emergency material security is the key to post-disaster emergency relief in complex environment engineering construction projects. Aiming at the emergency logistics center site path planning problem, the uncertain parameters of congestion time and maximum rescue time are described using trapezoidal fuzzy numbers, and the emergency logistics site path model of the two-phase engineering construction project is established. A quantum particle swarm optimization model is designed to avoid premature population convergence and maintain population diversity. The particle swarm algorithm uses the quantum spin gate’s rotation angle update to represent the particle velocity update. Taking the engineering construction project in the western mountainous area as an example, the validity and applicability of the model are verified through model comparison and sensitivity analysis. The results of the example show that in the complex environment, the quantum particle swarm algorithm takes 29.35 s in convergence time, and the particle swarm algorithm takes 40.12 s, which is 36.69% higher than the efficiency of PSO. In total cost, the quantum particle swarm algorithm has a total cost of 46,632.40 RMB, and the particle swarm algorithm has a total cost of 48,319.51 RMB, which is 3.62% lower than the cost of PSO. The quantum particle swarm algorithm’s total distance is 550.57 km, and the particle swarm algorithm’s total distance is 579.35 km, 5.23% lower than the total distance of PSO. The model established in this study can scientifically select the location of emergency facilities and formulate the emergency rescue path, reduce the response time of emergency rescue and storage costs, and provide decision support for the scheduling of emergency supplies for engineering construction projects in complex and dangerous areas.

OPPORTUNITIES AND RESULTS OF INTEGRATION OF KAZAKHSTAN'S TRANSPORT SYSTEM WITH INTERNATIONAL TRANSPORT SYSTEMS

The article examines the transport and transit industry of Kazakhstan, strategic planning for improving the logistics infrastructure, creating a network of multimodal transport and logistics centers integrated into regional transport and logistics systems, ensuring close integration of the Kazakh transport system as an equal partner with international transport systems. The main components of the logistics infrastructure of multimodal transport and logistics centers, international transport corridors that ensure coordinated interaction of modes of transport and other participants in the transport and logistics process in Kazakhstan are considered as strategic points for the development of the economy of Kazakhstan. Modern international transport corridors are becoming the main core of the effective development of interstate economic relations in the era of globalization of the world economy. This industry is considered as an important factor of socio-economic prosperity and the Republic of Kazakhstan, which is heading towards an innovative path of development. Because international transport corridors are one of the most important industries that contributes to the prosperity of the global economy, facilitating trade and exchange of goods between countries of the world.

Methodology for Researching the Synthesis of Transport and Logistics Systems of the Kyrgyz Republic

The article discusses the research methodology for the synthesis of transport and logistics systems, adapted to the specific conditions of the Kyrgyz Republic. The relevance of the study is due to the need to increase the competitiveness of the national economy and realize the country’s transit potential through the creation of an effective logistics infrastructure. The proposed methodology is based on the integrated application of modern theories and concepts from the field of transport logistics, modeling, geographic information systems, intelligent transport systems, as well as the principles of green logistics and sustainable development. Particular attention is paid to taking into account the features of the mountainous terrain of Kyrgyzstan and the need to integrate various modes of transport into multimodal transportation. The methodology provides for the creation of an optimal network of logistics centers and transport hubs that concentrate cargo flows and ensure their efficient processing. The implementation of information technologies and systems is considered as a key factor in the integration of supply chain participants, monitoring of transport flows, modeling and optimization of logistics processes. Successful implementation will create a competitive transport and logistics system, integrated into global supply chains and meeting modern requirements for efficiency and sustainable development.

Comprehensive multistage approach for measuring the efficiency of logistics processes in the presence of a mismatch between sales and logistics

Frequently, various sectors within the same company often find themselves at odds with one another due to conflicting objectives. For example, the sales and logistics departments frequently fail to synchronize, with sales viewing logistics merely as a cost center. Conversely, sales place demanding delivery tasks on logistics, particularly evident in scenarios involving out-of-stock or non-assortment items. To address this pervasive issue, the primary objective of this paper is to propose a model for assessing the efficiency of logistical processes, distribution centers, and drivers. Hence, it can be asserted that this study, through its proposed model, aims to accomplish several aims: (i) determine the effectiveness of distribution centers (DCs), (ii) analyze how the efficiency of DCs evolves over time, (iii) evaluate the performance of distribution drivers, and (iv) rank proficient drivers for bonus allocation based on their performance. To achieve these objectives, the suggested model relies on the application of the CI-DEA-Malmquist Index-DEA-MEREC-ADAM methodology. Specifically, the model is delineated into three distinct phases. The initial phase entails employing the CI-DEA and Malmquist index methodologies to condense the multitude of parameters considered in the study by utilizing the CI-DEA approach. Additionally, Malmquist analysis is applied to observe the multi factor productivity change in the efficiency of DCs and to identify the most efficient DC across all time periods. Following the identification of the most efficient DC, the subsequent phase focuses on selecting drivers from that center, followed by applying the DEA method to isolate only the most efficient drivers, who are then further evaluated and ranked accordingly. Through the application of these methodologies, it was determined that out of a total of 10 drivers, only four were deemed efficient. In the final phase of the model, these drivers were assessed based on seven criteria for ranking purposes. During this phase, the MEREC method was utilized to ascertain the criteria weights, while the ADAM method was employed for driver ranking. The findings revealed that the second driver ranked the highest and thus should be granted the highest bonus.

Enhancing Logistics Optimization

With the expansion of the logistics network, enterprise logistics distribution faces increasing challenges, including high transportation costs, low distribution efficiency, and unstable distribution networks. To address these issues, this study focuses on optimizing enterprise logistics distribution using a double-layer (DL) model. In this paper, we propose a DL model for optimizing enterprise logistics distribution. The DL model is designed to find the optimal solution using the particle swarm optimization (PSO) algorithm. By leveraging location data from the region, the DL model evaluates and compares alternative distribution centers to determine the most efficient distribution strategy. The results demonstrate that the DL site selection model developed in this study effectively addresses the tasks of logistics center location and distribution optimization among alternative distribution centers. Comparison tests reveal that the distribution path proposed by the DL model is more accessible and cost-effective compared to alternative approaches.