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Artykuły w czasopismach na temat „Logistics Clustering”

Autor: Grafiati

Data publikacji: 2 czerwca 2025

Data aktualizacji: 31 lipca 2025

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1

Rivera, Liliana, David Gligor, and Yossi Sheffi. "The benefits of logistics clustering." International Journal of Physical Distribution & Logistics Management 46, no. 3 (2016): 242–68. http://dx.doi.org/10.1108/ijpdlm-10-2014-0243.

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Purpose – The purpose of this paper is to analyze the benefits of logistics clustering, with the intent to explain their growth and popularity among private agents and policy makers during the last decade. Design/methodology/approach – Because of limited knowledge about the benefits of logistics clustering a main objective of this paper is theory building. The authors employed a grounded theory approach and conducted 135 open and semi structured interviews with logistics executives, government officials, academics, and chambers of commerce representatives. Findings – Study results revealed tha

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Tri Kismanti, Sinta, and Andi Ard Maidah. "Penentuan Kelompok Jaringan Logistik pada Wilayah Kepulauan menggunakan Fuzzy C-Means." Borneo Engineering : Jurnal Teknik Sipil 2, no. 2 (2018): 76. http://dx.doi.org/10.35334/be.v2i2.615.

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Indonesia as the island nation with territorial waters is one of the modes of transportation. For this condition, most of activities are conducted in marine, such as logistics distribution. The movement of logistics distribution will result in a movement pattern of the logistic. Determination of the optimal pattern of logistics movement network can support the smooth distribution system. Determination of logistic network patterns is done by clustering using Fuzzy C-means, clustering aims to get island groups in adjacent locations. The clustering process using Fuzzy C-Means obtained that the nu

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Mesa-Arango, Rodrigo, and Satish V. Ukkusuri. "Demand clustering in freight logistics networks." Transportation Research Part E: Logistics and Transportation Review 81 (September 2015): 36–51. http://dx.doi.org/10.1016/j.tre.2015.06.002.

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Yang, Pengbo. "Intelligent Analysis of Logistics Information Based on Dynamic Network Data." Journal of Control Science and Engineering 2022 (July 5, 2022): 1–9. http://dx.doi.org/10.1155/2022/7967040.

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In order to realize the intellectualization of logistics information analysis, this paper proposes an intelligent analysis method of logistics information based on dynamic network data cloud mining. This paper selects the data of a shipping logistics platform to realize the intelligent analysis experiment of logistics information based on cloud clustering mining. The purpose of the experiment is to find out the advantages of logistics information intelligent analysis based on cloud mining by comparing the performance differences between cloud clustering mining and traditional clustering mining

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Zhang, B. S., Z. Q. Xiang, H. Zhang, and R. Liu. "Trajectory Clustering Of Segmented Field Operations Logistics Process." Journal of Physics: Conference Series 2029, no. 1 (2021): 012120. http://dx.doi.org/10.1088/1742-6596/2029/1/012120.

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Abstract It has become a new research direction to use process mining technology to mine and analyze all kinds of data generated during shipbuilding. The classification of hull segments into different clusters according to some properties in advance can make the excavation results more specific. In this paper, the process examples in ship construction are divided into different clusters based on the cohesive hierarchical clustering algorithm. Firstly, this paper introduces the advantages and disadvantages of several main clustering algorithms, selects the clustering algorithm most suitable for

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6

Zhong, Jianying, Jibin Zhu, Yonghao Guo, Yunxin Chang, and Chaofeng Zhu. "A Customer Clustering Algorithm for Power Logistics Distribution Network Structure and Distribution Volume Constraints." International Journal of Circuits, Systems and Signal Processing 15 (August 25, 2021): 1051–56. http://dx.doi.org/10.46300/9106.2021.15.113.

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Customer clustering technology for distribution process is widely used in location selection, distribution route optimization and vehicle scheduling optimization of power logistics distribution center. Aiming at the problem of customer clustering with unknown distribution center location, this paper proposes a clustering algorithm considering distribution network structure and distribution volume constraint, which makes up for the defect that the classical Euclidean distance does not consider the distribution road information. This paper proposes a logistics distribution customer clustering al

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Wang, Shenxiang. "The Development Trend of China’s Agricultural Product Cold Chain Logistics from the Perspective of Big Data." Advances in Multimedia 2022 (November 17, 2022): 1–13. http://dx.doi.org/10.1155/2022/2253448.

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With the gradual prosperity of social economy, people’s demand for agricultural products consumption has also gradually increased. Through the efficient introduction of big data technology, we can optimize and innovate the management system of agricultural cold chain logistics enterprises, realize the modernization of enterprise logistics management, and effectively improve the management efficiency of agricultural cold chain logistics enterprises. Using big data technology can improve the efficiency of information docking, improve the stickiness of enterprise customers, and speed up the value

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Trappey, Charles V., Amy J. C. Trappey, Ai‐Che Chang, and Ashley Y. L. Huang. "Clustering analysis prioritization of automobile logistics services." Industrial Management & Data Systems 110, no. 5 (2010): 731–43. http://dx.doi.org/10.1108/02635571011044759.

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Mahesh Prabhu, R., G. Hema, Srilatha Chepure, and M. Nageswara Guptha. "Logistics Optimization in Supply Chain Management using Clustering Algorithms." Scalable Computing: Practice and Experience 21, no. 1 (2020): 107–14. http://dx.doi.org/10.12694/scpe.v21i1.1628.

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Today’s business environment, survival and making profit in market are the prime requirement for any enterprise due to competitive environment. Innovation and staying updated are commonly identified two key parameters for achieving success and profit in business. Considerably supply chain management is also accountable for profit. As a measure to maximize the profit, supply chain process is to be streamlined and optimized. Appropriate grouping of various suppliers for the benefit of shipment cost reduction is proposed. Data relating to appropriate attributes of supplier logistics are collected

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Grytsenko, Sergiy, and Veronika Ninich. "Clustering of logistics supply chains in the process of Ukraine's eurointegration." Electronic Scientific Journal Intellectualization of Logistics and Supply Chain Management #1 2020 1, no. 20 (2023): 46–57. http://dx.doi.org/10.46783/smart-scm/2023-20-5.

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This article delves into the concept of clusters within the nation's economy, the role of logistics management in effective cluster operation, and avenues for its enhancement. The research focuses on the socio-economic processes that facilitate the clustering of logistics supply chains for the company "PAPIR SERVICE SK" - one of Ukraine's largest companies involved in the procurement and distribution of paper and cardboard in rolls. The subject of investigation encompasses a comprehensive range of scientific, methodological, and practical aspects related to the establishment of a mechanism for

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11

Wang, Ping, Xianjun Chen, and Xuebin Zhang. "Research on Location of Logistics Distribution Center Based on K-Means Clustering Algorithm." Security and Communication Networks 2022 (July 9, 2022): 1–9. http://dx.doi.org/10.1155/2022/2546429.

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The basic task of the logistics distribution center is to achieve the storage and distribution of materials, and to plan, implement, and manage the effective flow of materials from the supplying place to the consumption place. Scientific location of logistics distribution center can effectively reduce logistics cost, improve the speed of circulation, increase the profits of enterprises, and enhance the core competitiveness of enterprises. Combining the advantages of K-means clustering algorithm, this paper applies it to the location problem of logistics distribution center and proposes a logis

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12

Wang, Jiwei. "An Empirical Study of Logistics Industry Clustering on Regional Economic Growth in Liaoning Province." Advances in Economics and Management Research 8, no. 1 (2023): 164. http://dx.doi.org/10.56028/aemr.8.1.164.2023.

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Using the relevant data of Liaoning Province from 2010 to 2021, an econometric model is established with the C-D production function as the theory combined with the new economic theory, and dummy variables are introduced according to the three degrees of logistics industry agglomeration and the division of the three major economic zones in Liaoning Province, to explore the effect of logistics industry agglomeration on the promotion of regional economic growth under different degrees of agglomeration and economic zones. It is found that the clustering of logistics industry has a significant eff

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13

KARA, Karahan. "Clustering of Developing Countries in Terms of Logistics Market Development with Fuzzy Clustering and Discriminant Analysis." Journal of Yaşar University 18, no. 69 (2023): 19–40. http://dx.doi.org/10.19168/jyasar.1149970.

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Logistics performance indicators are important in determining the market development levels of countries. Especially the logistics markets of developing countries play an active role in increasing the country's economy and trade volumes. In this research, it is aimed to cluster the developing countries according to their level of logistics market development in 2022. For this reason, fuzzy clustering and discriminant analyzes have been applied in the research. The sample area of the study consists of 50 developing countries. The data of the research have been taken from The Agility Emerging Ma

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14

Abushaikha, Ismail. "The influence of logistics clustering on distribution capabilities: a qualitative study." International Journal of Retail & Distribution Management 46, no. 6 (2018): 577–94. http://dx.doi.org/10.1108/ijrdm-01-2018-0018.

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PurposeThe purpose of this paper is to explore why and how firms with logistics-intensive operations such as fast-moving consumer good (FMCG) distributors benefit from residing in logistics clusters. In particular, this study seeks to fill a gap in the understanding of how logistics clustering may influence FMCG firms’ distribution capabilities.Design/methodology/approachThree case studies of FMCG distributors geographically agglomerated within Q Logistics Cluster in Jordan serve to elaborate the existing theory of clustering. Data were collected from 24 interviews as well as observational evi

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15

Škultéty, Filip, Dominika Beňová, and Jozef Gnap. "City Logistics as an Imperative Smart City Mechanism: Scrutiny of Clustered EU27 Capitals." Sustainability 13, no. 7 (2021): 3641. http://dx.doi.org/10.3390/su13073641.

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In large urban agglomerations, various logistical problems arise due to high population density and deficient transport infrastructure. City logistics involves the efficient distribution of freight transport in urban areas and approaches to mitigate environmental impacts and traffic congestion. This paper aims to use a two-step cluster analytic approach to segmentation of EU27 capital cities based on their city logistics performance. To obtain primary outcomes, the log-likelihood measure in SPSS Statistics was used. The results can be used to identify the development and implementation of logi

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16

Ouyang, Bai Cheng. "Research on the Automatic Routing Technology in the Logistics System and IOT." Applied Mechanics and Materials 608-609 (October 2014): 665–69. http://dx.doi.org/10.4028/www.scientific.net/amm.608-609.665.

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With the rapid development of logistics enterprises, tradition logistics sorting has been unable to meet the needs of the development of express logistics. Combining with the RFID technology, the paper proposes a new way of logistics sorting and data routing. By increasing the RFID tag and the AWB in the express waybill will improve efficiency. Using Cluster head selection principle and clustering algorithm of LEACH (adaptive clustering hierarchy). Comparison with original system, verified the practicability of RFID technology and data routing algorithm in the sorting system and easy to use.

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Zhou, Xiao, Jun Wang, Wenbing Liu, Fan Jiang, and Rui Li. "Intelligent Emergency Logistics Route Model Based on Cellular Space AGNES Clustering and Symmetrical Fruit Fly Optimization Algorithm." Symmetry 17, no. 5 (2025): 649. https://doi.org/10.3390/sym17050649.

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In response to the current research status and existing problems of material distribution during major emergency events, we construct an intelligent emergency logistics route model based on cellular space AGNES clustering (AGglomerative NESting clustering) and a symmetrical fruit fly optimization algorithm. We establish the cellular algorithm based on urban road nodes and node local spaces, and construct the topology algorithm to implement the cellular space in a way that includes distribution centers and delivery points. In the cellular space, we develop an improved AGNES clustering algorithm

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Lin, Tsung-Xian, Zhong-huan Wu, and Wen-Tsao Pan. "Optimal location of logistics distribution centres with swarm intelligent clustering algorithms." PLOS ONE 17, no. 8 (2022): e0271928. http://dx.doi.org/10.1371/journal.pone.0271928.

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A clustering algorithm is a solution for grouping a set of objects and for distribution centre location problems. But the common K-means clustering algorithm may give local optimal solutions. Swarm intelligent algorithms simulate the social behaviours of animals and avoid local optimal solutions. We employ three swarm intelligent algorithms to avoid these solutions. We propose a new algorithm for the clustering problem, the fruit-fly optimization K-means algorithm (FOA K-means). We designed a distribution centre location problem and three clustering indicators to evaluate the performance of al

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Huang, Heshan. "Route Planning of Freight Transport and Logistics Considering Truck Platooning." Advances in Economics, Management and Political Sciences 123, no. 1 (2024): 63–71. http://dx.doi.org/10.54254/2754-1169/123/2024mur0112.

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This article explores the integration of truck platooning and clustering algorithms within logistics path planning. Clustering algorithms divide a specific area into several zones, each with a designated distribution center for further route planning. This approach ensures that the route planning process extends the distance that truck fleets can travel together in platoon formation, maximizing the benefits of truck platooning. The integration of clustering and platooning not only enhances environmental sustainability by reducing fuel consumption and emissions but also increases operational ef

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Santos Lima, Fabiana, Daniel de Oliveira, Mirian Buss Gonçalves, and Márcia Marcondes Altimari Samed. "Humanitarian Logistics: A Clustering Methodology for Assisting Humanitarian Operations." Journal of technology management & innovation 9, no. 2 (2014): 86–97. http://dx.doi.org/10.4067/s0718-27242014000200007.

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Fu, Pei-hua, and Hong-bo Yin. "Logistics Enterprise Evaluation Model Based On Fuzzy Clustering Analysis." Physics Procedia 24 (2012): 1583–87. http://dx.doi.org/10.1016/j.phpro.2012.02.233.

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He, Yan. "Study on Secure Dynamic Covering Algorithm for E-Logistics Information in a Cloud Computing Platform." International Journal of Information Technology and Web Engineering 12, no. 4 (2017): 42–55. http://dx.doi.org/10.4018/ijitwe.2017100103.

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For traditional coverage method, local adaptive weighted search is adopted for subspace reconstruction of e-logistics information, which requires significant iterative computations and leads to large coverage errors and unsatisfactory results. This paper proposes a secure dynamic covering algorithm for e-logistics information based on the basis of directional clustering for the envelope of optimization solution vectors. A data network distribution model of e-logistics information on a cloud computing platform is constructed to extract features of e-logistics information and to construct time s

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Paksadze, I. "CLUSTER ANALYSIS OF THE LOGISTICS SECTOR: A CASE STUDY OF GEORGIA." Sciences of Europe, no. 164 (May 14, 2025): 33–36. https://doi.org/10.5281/zenodo.15401272.

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Driven by the dynamics of globalization, the logistics sector has emerged as a critical determinant of national competitiveness. Georgia, owing to its strategic geographical positioning, holds significant potential as a regional logistics hub. This study aims to investigate the spatial development of the logistics sector across Georgia’s regions and to assess the country’s logistics competitiveness from a regional perspective. To quantify the degree of regional concentration within the sector, the Location Quotient (LQ) methodology is applied. The research incorporates a review of

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Yu, Hang, and Kai Zhang. "Agricultural Logistics Companies Distribution Based on Fuzzy Clustering Analysis and Genetic Algorithm." Applied Mechanics and Materials 644-650 (September 2014): 2276–80. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.2276.

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This paper analyzes the logistics distribution system, logistics and distribution of agricultural products and agricultural products logistics enterprise status,Demand for agricultural products logistics companies point clustering analysis, Determine the economic and non-economic rational and reasonable point point,To TSP problem-based, Application of improved genetic algorithm to determine its distribution route, Use natural number coding chromosome structure represents feasible route, greedy crossover, mutation and reverse the 2-opt other methods, With VC + + and MATLAB programming of the al

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Taranenko, O. "METHODOLOGICAL ASPECTS OF LOCATION OF LOGISTICS CENTERS OF COURIER AND POSTAL SERVICES." THEORETICAL AND APPLIED ISSUES OF ECONOMICS, no. 47 (2023): 204–11. http://dx.doi.org/10.17721/tppe.2023.47.19.

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The task of finding organizational reserves to increase the efficiency of business processes of logistics companies by optimizing the movement of material flows is considered. The focus on organizational reserves, the implementation of which requires the involvement of minimal investments compared to other types of reserves, considering the limited access to sources of financial resources in the conditions of martial law, is rational. At the level of individual logistics companies, one of the areas of implementation of organizational reserves is solving the problem of optimal placement of logi

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Deng, Ju Li, and Guo Rong Chen. "Research on Logistics Modeling Method Based on Complex Network Theories." Applied Mechanics and Materials 58-60 (June 2011): 1210–13. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.1210.

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In order to resolve the modeling method of logistics network, a basic model named NGM is presented. According to some special characteristics of the real logistics network such as growth, preferential attachment, edge-weighted, and clustering, the basic model is improved and optimized. The modeling method of logistics is analyzed and simulated too. The results of the simulation show that the modeling method is more effective than the traditional logistics modeling theories.

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Jiao, Hongzan, Faxing Yang, Shasha Xu, and Shibiao Huang. "Using Large-Scale Truck Trajectory Data to Explore the Location of Sustainable Urban Logistics Centres—The Case of Wuhan." ISPRS International Journal of Geo-Information 12, no. 3 (2023): 88. http://dx.doi.org/10.3390/ijgi12030088.

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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

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M, Akhil Nilavan. "AI Based Customized Time Slot Delivery Of Parcels." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 01 (2025): 1–9. https://doi.org/10.55041/ijsrem40015.

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In the age of rapidly growing e-commerce and increasing customer expectations, optimizing last-mile delivery has become a significant challenge for logistics and courier services. This paper presents a comprehensive framework for an AI-based customized time slot delivery system aimed at enhancing operational efficiency and customer satisfaction. Leveraging artificial intelligence (AI), clustering algorithms, and route optimization techniques, the system enables customers to select delivery slots based on their availability. By integrating dynamic data analysis, real-time communication, and int

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Panjehfouladgaran, Hamidreza, and Stanley Frederick W. T. Lim. "Reverse logistics risk management: identification, clustering and risk mitigation strategies." Management Decision 58, no. 7 (2020): 1449–74. http://dx.doi.org/10.1108/md-01-2018-0010.

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PurposeReverse logistics (RL), an inseparable aspect of supply chain management, returns used products to recovery processes with the aim of reducing waste generation. Enterprises, however, seem reluctant to apply RL due to various types of risks which are perceived as posing an economic threat to businesses. This paper draws on a synthesis of supply chain and risk management literature to identify and cluster RL risk factors and to recommend risk mitigation strategies for reducing the negative impact of risks on RL implementation.Design/methodology/approachThe authors identify and cluster ris

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Singh, Gulshanara, Carmelita Gorg, and Andreas Timm Giel. "Clustering and routing model for transport logistics using software agents." International Journal of Logistics Systems and Management 10, no. 2 (2011): 180. http://dx.doi.org/10.1504/ijlsm.2011.042627.

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Liu, Shiming, and Huihong Chen. "Research on Multi-objective clustering Optimization of Logistics Distribution Line." IOP Conference Series: Materials Science and Engineering 612 (October 19, 2019): 042078. http://dx.doi.org/10.1088/1757-899x/612/4/042078.

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Zhuang, Zhi Jie. "Inventory Information Management of Logistics Supply Chain." Advanced Materials Research 989-994 (July 2014): 5453–56. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.5453.

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The supply chain information management of logistics has become an important method to enhance its competitiveness. The inventory information management and application of the logistics supply is researched based on grey clustering decision-making methods. The inventory theory and methods are studied firstly, and the fuzzy mathematics and grey system theory are used to solve the classification problem. The electronic industry logistics supply chain is taken as the example, the inventory information management problem is solved. The inventory information management theory is improved in this pa

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Yuliana, Naning, Budisantoso Wirjodirjo, and Ahmad Rusdiansyah. "Optimizing Indonesian Pioneering Maritime Network through Port Clustering." IOP Conference Series: Earth and Environmental Science 1461, no. 1 (2025): 012026. https://doi.org/10.1088/1755-1315/1461/1/012026.

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Abstract Indonesia’s unique geography, characterized by scattered islands, presents challenges for maritime logistics, particularly in remote and border areas. To address these challenges, this study proposes a K-Medoids clustering model to optimize the pioneering maritime network, which is crucial for logistics distribution and population mobility in Eastern Indonesia. Unlike previous deterministic models, this approach groups ports based on their spatial characteristics, aiming to enhance network efficiency and resilience. By analyzing the coordinates of 512 ports, the model identified 10 op

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Chen, Liang, Xingwei Wang, and Jinwen Shi. "Clustering Control of Multi-Objective Problems with Application to E-commerce." International Journal of Robotics and Control 1, no. 1 (2018): 41. http://dx.doi.org/10.5430/ijrc.v1n1p41.

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In the existing logistics distribution methods, the demand of customers is not considered. The goal of these methods is to maximize the vehicle capacity, which leads to the total distance of vehicles to be too long, the need for large numbers of vehicles and high transportation costs. To address these problems, a method of multi-objective clustering of logistics distribution route based on hybrid ant colony algorithm is proposed in this paper. Before choosing the distribution route, the customers are assigned to the unknown types according to a lot of customers attributes so as to reduce the s

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Bai, Shizhen, and Hongbin Sun. "Research on Enterprise Supply Chain Optimization Model and Algorithm Based on Fuzzy Clustering." Journal of Mathematics 2021 (December 28, 2021): 1–9. http://dx.doi.org/10.1155/2021/4827903.

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Reasonable logistics distribution network structure can not only effectively reduce the cost of logistics enterprises themselves but also reduce the social cost. Through effective supply chain management, enterprises can significantly reduce costs, improve competitiveness, and enhance their ability to resist risks. Because the single-level distribution network structure of production enterprises is not suitable for large-scale logistics distribution, this paper proposes a distribution network structure design that accords with economies of scale and establishes an enterprise supply chain optim

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HUANG, J. K. "B2C E-COMMERCE CUSTOMIZED LOGISTICS AREA INVENTORY ALLOCATION STRATEGY BASED ON CONSTRAINED CLUSTERING ALGORITHM." Latin American Applied Research - An international journal 48, no. 3 (2018): 217–22. http://dx.doi.org/10.52292/j.laar.2018.231.

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Logistics network includes regional logistics network and urban logistics network. In this paper, the urban logistics network is taken as the research object. With the improvement of the consumption level of the residents, the attention to quality has become an important reference standard for consumers to choose e-commerce, which makes the electric business shift from "price war" to "service war". Compared with past purchases in physical stores, most consumers prefer to choose convenient and fast online shopping. As a result, the size of the online shopping market has increased rapidly. Accor

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Ma, Zhanxin, Xiyu Zheng, Hejun Liang, and Ping Luo. "Logistics Center Selection and Logistics Network Construction from the Perspective of Urban Geographic Information Fusion." Sensors 24, no. 6 (2024): 1878. http://dx.doi.org/10.3390/s24061878.

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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 ur

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Zhang, Yuhang, and Tiantian Tan. "Optimization of Organ Transplantation Logistics from an Operations Research Linear Programming Perspective." Advances in Economics and Management Research 10, no. 1 (2024): 77. http://dx.doi.org/10.56028/aemr.10.1.77.2024.

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Logistics is crucial in organ transplantation surgeries, focusing on maximizing donor-recipient matches within organ survival timeframes. This study explores the impact of clustering structures on organ matches, utilizing dynamic analysis and novel mathematical models to evaluate transportation modes and prioritize intra-regional organ transplantation while meeting time constraints. Initially concentrating on maximizing flow within a single timeframe, the study addresses disparate outcomes across organ types by developing an additional model for maximizing flow across multiple organ types. Com

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Li, Zhaoqing, Jinbing Wang, and Lei Zhang. "Flexible Logistics Sorting System Allocation via Hybrid GA-PSO with Dynamic Clustering." Journal of Innovation and Development 10, no. 3 (2025): 11–18. https://doi.org/10.54097/62beh769.

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To address the challenges posed by the large sorting volume of cigarettes in tobacco logistics distribution centers and the significant impact of cigarette specification allocation on the overall processing time of orders, this study aims to optimize the allocation of each sorting zone and enhance sorting efficiency. A mathematical model is developed with the objective of minimizing the similarity coefficients of specifications within each zone, which is then solved using an enhanced genetic particle swarm dynamic clustering (GA-PSO-K) algorithm. Initially, the similarity coefficient of each s

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Liu, Xiao Lan, and Wu Yi Zhang. "Application of Composite Ant Colony Optimization in Logistics Distribution Center Location." Applied Mechanics and Materials 253-255 (December 2012): 1476–81. http://dx.doi.org/10.4028/www.scientific.net/amm.253-255.1476.

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A new model called location, routing, production and sale problem(LRPSP) is proposed for logistics distribution center location in the paper. In this model vehicle routing problem(VRP) and the balance or imbalance problem of production and sale are considered, because all these would influence the selection of locations of logistics distribution centers. And also ant colony optimization(ACO) for clustering and ACO for finding the shortest route are introduced to assign clients to distribution centers and solve VRP respectively for the model. Through designing the transition probability, the ta

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Abdulhameed, Osamah, Sali Ghanem, Rafal Sadeq, Reemas Al Ghamdi, Dalal Al Mazyad, and Naveed Ahmed. "Designing of a dynamic logistics platform for optimization of truck assignment and its route for KINZA company." Decision Science Letters 14, no. 2 (2025): 327–38. https://doi.org/10.5267/j.dsl.2025.1.005.

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A consideration of the integral variables of customer location, traffic flow, and road conditions to determine the best feasible delivery routes is a big challenge in Logistical operations. A poor routing strategy that delivers products places an ineffective gloss and eventually converts into high operating expenses, over-consumption of fuel, and shipment delays. The paper’s goal is to build a model for the logistics management of the company which aims for effective management of the truck allocation and vehicle routing using K-means clustering and TSP. K-means clustering is often used to cla

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Kleineidam, Julia. "Distinguishing Organisational Profiles of Food Loss Management in Logistics." Logistics 6, no. 3 (2022): 61. http://dx.doi.org/10.3390/logistics6030061.

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Background: Food loss management (FLM), which is discussed at length in the literature, lacks a scientific basis on which to determine the current engagement of actors in the food value chain and what is relevant to derive appropriate measures according to the circumstances in the organisations concerned. Therefore, this paper aims to derive patterns by which the engagement of actors can be distinguished and, on this basis, to make recommendations for further action. Methods: Based on an online survey of 40 participants, a clustering analysis was conducted using the unsupervised learning metho

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Zhou, Yewang. "The Research on Supplier Selection Model of the Third Party Logistics Based on Grey Clustering." International Journal of Modeling and Optimization 4, no. 6 (2014): 489–92. http://dx.doi.org/10.7763/ijmo.2014.v4.422.

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Karpenko, Oksana Oleksandrivna, and Olena Mykhailivna Palyvoda. "MECHANISM OF PROVIDING ECONOMIC DEVELOPMENT OF TRANSPORT AND LOGISTICS ENTERPRISES ON THE BASIS OF CLUSTERING." SCIENTIFIC BULLETIN OF POLISSIA 2, no. 4(12) (2017): 33–39. http://dx.doi.org/10.25140/2410-9576-2017-2-4(12)-33-39.

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Acar, A. Zafer. "Proposing of a port-centric hierarchical logistics clustering model for Turkey." International Journal of Logistics Economics and Globalisation 8, no. 2 (2020): 110. http://dx.doi.org/10.1504/ijleg.2020.10030247.

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Acar, A. Zafer. "Proposing of a port-centric hierarchical logistics clustering model for Turkey." International Journal of Logistics Economics and Globalisation 8, no. 2 (2020): 110. http://dx.doi.org/10.1504/ijleg.2020.108189.

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Liu, Su-Yu, Cheng Li, Yi-Ping Feng, and Gang Rong. "Clustering structure and logistics: A new framework for supply network analysis." Chemical Engineering Research and Design 91, no. 8 (2013): 1383–89. http://dx.doi.org/10.1016/j.cherd.2013.02.021.

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管, 玉洁. "Location of Emergency Logistics Center Based on K-Means Clustering Algorithm." Pure Mathematics 09, no. 07 (2019): 809–12. http://dx.doi.org/10.12677/pm.2019.97106.

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Anbuudayasankar, S. P., K. Ganesh, S. C. Lenny Koh, and K. Mohandas. "Clustering-based heuristic for the workload balancing problem in enterprise logistics." International Journal of Value Chain Management 3, no. 3 (2009): 302. http://dx.doi.org/10.1504/ijvcm.2009.028605.

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Zheng, Kangning, Xiaoxin Huo, Sajjad Jasimuddin, Justin Zuopeng Zhang, and Olga Battaïa. "Logistics distribution optimization: Fuzzy clustering analysis of e-commerce customers’ demands." Computers in Industry 151 (October 2023): 103960. http://dx.doi.org/10.1016/j.compind.2023.103960.

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