Relevant bibliographies by topics / Inventory and distribution logistics

Academic literature on the topic 'Inventory and distribution logistics'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Inventory and distribution logistics"

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Li, Xiaoli. "Application of Collaborative Optimization in Urban Fresh Product Logistics Inventory and Distribution System." Scientific Programming 2022 (September 9, 2022): 1–14. http://dx.doi.org/10.1155/2022/4516499.

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People’s requirements for material needs and living standards are gradually increasing, and consumers’ demand for fresh, fruit, and vegetable cold chain foods is also increasing. This paper takes urban fresh agricultural products cold chain logistics as the research object, establishes a collaborative optimization model of urban fresh agricultural products cold chain logistics inventory and distribution based on distribution centers, proposes a partitioning solution strategy for the multidistribution center problem, and proposes a collaborative optimization in urban fresh agricultural products logistics inventory and distribution system. The application of collaborative optimization in urban fresh product logistics inventory and distribution system is proposed.
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Dachyar, Muhammad, Yadrifil Yadrifil, and Idrus Fahreza. "INVENTORY MANAGEMENT DESIGN FOR A RAPID DISASTER RELIEF, TOWARDS INTERNET OF THINGS (IOT) POTENTIAL." EUREKA: Physics and Engineering 6 (November 30, 2019): 9–18. http://dx.doi.org/10.21303/2461-4262.2019.001079.

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All victims in a disaster situation need rapid assistance, yet in some cases this goal not accompanied by an ideal recording system on their logistic inventory management. This study aims to achieve inventory management systems for disaster logistics and their delivery in a fast response time and to create a rapid disaster relief distribution process through the implementation of Internet of Things (IoT). In disaster management agencies, the Business Process Reengineering (BPR) approach and IoT implementation are used. The proposed model resulted in a 44.92 percent increase in the time efficiency of logistical relief distribution, which previously took 64.34 hours to 35.44 hours.
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Kamphues, J., and T. Hegmanns. "A modular approach for integrated inventory management in distribution logistics." IFAC-PapersOnLine 48, no. 3 (2015): 1815–20. http://dx.doi.org/10.1016/j.ifacol.2015.06.350.

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Raghuram, G. "Logistics Management: An Introductory Note." Vikalpa: The Journal for Decision Makers 17, no. 1 (January 1992): 31–37. http://dx.doi.org/10.1177/0256090919920104.

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Logistics is a logical extension of viewing transportation along with production planning, distribution network design, location of plants and warehouses, inventory management and so on to achieve an efficient goods distribution system. This article by G Raghuram, which identifies key actors involved in logistics in the Indian context and concludes that the potential for cost reduction in logistics is substantial, could pave the way for further work in this area.
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Dong, Bo, Manzhen Duan, and Yinfeng Li. "Exploration of Joint Optimization and Visualization of Inventory Transportation in Agricultural Logistics Based on Ant Colony Algorithm." Computational Intelligence and Neuroscience 2022 (June 15, 2022): 1–12. http://dx.doi.org/10.1155/2022/2041592.

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The problem of joint optimization of inventory and transportation in agricultural logistics and distribution is a typical logistics problem, but agricultural logistics and distribution also have their own characteristics, such as uneven distribution of outlets, complex road conditions, very many outlets, a single order with few goods but high frequency of ordering, centralized distribution, and unified channels. To promote the sustainable development of the economy, it is necessary to save energy and reduce emissions, and eventually enter a new era of “low consumption, low pollution, and low emissions.” Modern logistics vehicle-scheduling process is complex and changeable, and the existing mathematical methods are not perfect in solving this problem, lacking scientific theory as a guide. The joint optimization problem introduces the inventory change factor on the basis of periodic vehicle path optimization and optimizes the inventory decision and path planning in an integrated manner. As a system to support the logistics industry, the visualized logistics information system is capable of video viewing and querying logistics information. In order to reduce gas emissions and save costs, it is necessary to optimize the transportation link, and the focus of optimization is the route optimization of distribution vehicles. Ant colony algorithm (ACA) is an emerging search and optimization technique, which emerged from the research of ACA. In this study, we study the joint optimization and visualization of inventory transportation in agricultural logistics based on ACA. In addition, the experimental results show that the inventory cost/total cost of improved ACA is 0.006 when the unit mileage transportation cost is 10, and the IBM ILOG CPLEX is 0.031, which is reduced by 0.0025, that is to say, in the case of high inventory cost per unit product, the use of improved ACA can lead to a significant reduction in inventory costs. Therefore, it can realize the whole process of control, traceability, and dynamic optimization to ensure the timeliness of emergency finished food security and provide real-time information for decision-making in command as well.
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Pei, Ying Mei, Chun Ming Ye, and Li Hui Liu. "Inventory-Transportation Integrated Optimization Problem." Applied Mechanics and Materials 178-181 (May 2012): 2793–97. http://dx.doi.org/10.4028/www.scientific.net/amm.178-181.2793.

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In view of typical many-one distribution network in the modern distribution logistics system, the mathematic model on the inventory-transportation integrated optimization problem with stochastic demand and diversified products was established by using a bi-level programming method. Both decisions of inventory control and transportation arrangement were made at the same time. An improved heuristic algorithm was proposed to divide the integration problem into both problems of the inventory and the transportation: the cost were distributed by the former according to different products and the optimized cost was sought out by the latter according to different periods, thus the inventory-transportation integrated optimization problem was solved through the repeated iteration between the former and the latter. The mathematic description and the heuristic algorithm to the massive practice of the modern distribution logistics system are realized.
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Kmiecik, Mariusz. "Logistics Coordination Based on Inventory Management and Transportation Planning by Third-Party Logistics (3PL)." Sustainability 14, no. 13 (July 4, 2022): 8134. http://dx.doi.org/10.3390/su14138134.

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Currently, there is still a strong trend in research and in the market connected with the role of 3PL (third-party logistics) companies and the trend of developing and creating coordination in logistics networks. The most important issue for the following paper is the examination of the 3PL enterprise, which is able to create the demand forecasts to gain the functions of logistics coordination in the fields of inventory management and transportation planning. This research paper focuses on showing the demand forecasting tool results for 29 chosen distribution networks (in this paper, the traditional forecasting methods were used based on time series exponential smoothing, ARIMA, machine learning and neural-network-based methods, created in the R programming environment). In the next steps, the forecasting results were compared in the conditions of transportation planning and inventory management (in the conditions of “future” dynamic ABC analysis). The forecasting function supports the inventory management and transportation planning activity of 3PL as a key element of logistics coordination in distribution networks. The proper way to transfer the results of forecasting to an ABC analysis and transportation planning concept is to create a cloud-based system supported by data from the WMS (warehouse management system), while providing the possibility of results visualization by using some BI (business intelligence) solutions or different tools to create managerial information dashboards. Currently, one of the most efficient models connected with logistics coordination is the centralized network with 3PL responsible for planning and executing logistics processes with the creation of additional value. As such, 3PL is able to create a similar forecast for different types of DN and with different aggregations (per SKU or per recipient). It could support coordination in DN from the point of view of inventory management and transportation planning.
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Lv, Pin, and Cheng Zheng Ma. "The Choice of Different Logistics Policies Considering Transportation and Inventory Costs in a Two-Echelon Distribution System." Applied Mechanics and Materials 505-506 (January 2014): 902–6. http://dx.doi.org/10.4028/www.scientific.net/amm.505-506.902.

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This paper presented a formal analysis for the alternative of logistics centralization and decentralization policy in a two-echelon distribution system. First, functions of transportation and inventory costs under different policies in the system were developed. Second, the differences between transportation and inventory costs were compared, and the relationship between transportation and inventory cost difference was analyzed through a balance ratio. At last, some indicators were derived to measure the level of demand uncertainty, the amount of retailers and the size of customer orders. It shows that the optimal logistics policy can be determined as a tradeoff between transportation and inventory costs. And the indicators can provide a basis for selecting the optimal logistics policy.
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Antipenko, V. S., N. S. Babich, and K. V. Galkin. "Optimisation of Inventory Levels as Logistics Challenge." World of Transport and Transportation 19, no. 2 (November 13, 2021): 64–68. http://dx.doi.org/10.30932/1992-3252-2021-19-2-9.

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Inventory ensures stability of the production technical system. Production facilities have warehouses for workpieces to create final output parts, and warehouses for finished products to meet customer demand. Stocks of workpieces avoid manufacturing downtime. Stocks of finished products make it possible to meet demand in a timely manner and avoid penalties for late deliveries of finished products to consumers.On the other hand, the objects that make up the inventory are «dead» material resources that do not bring profit and negatively affect economic efficiency and competitiveness. According to published data, in economically developed countries, such as the USA, Japan, Germany and others, up to 30–40 % of production is in stocks. All this indicates the relevance of the issue of optimising the level of reserves, of solving the problem of establishing and maintaining the optimal level of the stock, its timely replenishment, considering time required for execution of applications of end users.The objective of the work is to propose a solution to a stochastic logistic problem of inventory management with a random time delay and random demand, obtained by the authors using the methods of mathematical statistics, mathematical modelling, and production logistics for unknown and arbitrary form of distribution functions of demand and time delay. The work provides specific examples of approaches to implementation of suggested solution.
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Qin, Zhidan. "The Inventory Control System of Reverse Logistics for E-Commerce Packaging Recovery Based on BP Neural Network." International Journal of Circuits, Systems and Signal Processing 16 (January 13, 2022): 413–25. http://dx.doi.org/10.46300/9106.2022.16.51.

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The paper combines BP neural network to optimize the control system of e-commerce packaging and reverse logistics inventory. Through improving the hardware configuration structure of the system, the system can be improved and the operation effect of the system can be improved. The software flow and operation algorithm of the storage control system of e-commerce packaging recycling reverse logistics are optimized step by step, and the logistics is delivered by following the vehicle on the spot and visiting the logistics The distribution personnel collect the relevant data and data in the process of logistics and transportation, draw the reverse logistics business flow chart, point out the situation of reverse logistics before and after the goods distribution and distribution due to the cancellation of orders or transactions by customers, and the application for return of goods after the transaction. Meanwhile, it points out that the sales return operation site in the reverse logistics management process is chaotic and not formed the clear business process specification and other problems can effectively control the reverse logistics inventory of e-commerce packaging recovery. Finally, the experiment proves that the e-commerce packaging recycling reverse logistics inventory control system is more practical in the practical application process, and fully meets the research requirements.
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Dissertations / Theses on the topic "Inventory and distribution logistics"

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Ekşioğlu, Sandra Duni. "Optimizing integrated production, inventory and distribution problems in supply chains." [Gainesville, Fla.] : University of Florida, 2002. http://purl.fcla.edu/fcla/etd/UFE0000529.

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Schmidt, Jeffrey A. NuDelman Devon D. "The Strategic Distribution Management Initiative and its effects on inventory levels and readiness /." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2002. http://library.nps.navy.mil/uhtbin/hyperion-image/02Dec%5FSchmidt.pdf.

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Farrokhvar, Leily. "Strategic Planning Models and Approaches to Improve Distribution Planning in the Industrial Gas Industry." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/79814.

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The industrial gas industry represents a multi-billion dollar global market and provides essential product to manufacturing and service organizations that drive the global economy. In this dissertation, we focus on improving distribution efficiency in the industrial gas industry by addressing the strategic level problem of bulk tank allocation (BTA) while considering the effects of important operational issues. The BTA problem determines the preferred size of bulk tanks to assign to customer sites to minimize recurring gas distribution costs and initial tank installation costs. The BTA problem has a unique structure which includes a resource allocation problem and an underlying vehicle routing problem with split deliveries. In this dissertation, we provide an exact solution approach that solves the BTA problem to optimality and recommends tank allocations, provides a set of delivery routes, and determines delivery amounts to customers on each delivery route within reasonable computational time. The exact solution approach is based on a branch-and-price algorithm that solves problem instances with up to 40 customers in reasonable computational time. Due to the complexity of the problem and the size of industry representative problems, the solution approaches published in the literature rely on heuristics that require a set of potential routes as input. In this research, we investigate and compare three alternative route generation algorithms using data sets from an industry partner. When comparing the routes generation algorithms, a sweep-based heuristic was the preferred heuristic for the data sets evaluated. The existing BTA solution approaches in the literature also assume a single bulk tank can be allocated at each customer site. While this assumption is valid for some customers due to space limitations, other customer sites may have the capability to accommodate multiple tanks. We propose two alternative mathematical models to explore the possibility and potential benefits of allocating multiple tanks at designated customer site that have the capacity to accommodate more than one tank. In a case study with 20 customers, allowing multiple tank allocation yield 13% reduction in total costs. In practice, industrial gas customer demands frequently vary by time period. Thus, it is important to allocate tanks to effectively accommodate time varying demand. Therefore, we develop a bulk tank allocation model for time varying demand (BTATVD) which captures changing demands by period for each customer. Adding this time dimension increases complexity. Therefore, we present three decomposition-based solution approaches. In the first two approaches, the problem is decomposed and a restricted master problem is solved. For the third approach, a two phase periodically restricting heuristic approach is developed. We evaluate the solution approaches using data sets provided by an industrial partner and solve the problem instances with up to 200 customers. The results yield approximately 10% in total savings and 20% in distribution cost savings over a 7 year time horizon. The results of this research provide effective approaches to address a variety of distribution issues faced by the industrial gas industry. The case study results demonstrate the potential improvements for distribution efficiency.
Ph. D.
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Loree, Nicholas A. "Integrating Deprivation Costs into Location-Allocation Model with Point-to-Point Distribution." Ohio University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1504264228262829.

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Bartes, Lukáš. "Studie logistické koncepce v podniku." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2007. http://www.nusl.cz/ntk/nusl-221490.

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Master´s thesis is solved in business enterprise focused on end user, proceeding demand prognosis. With concentration on solution and optimizing transport costs in options (production enterprise inventory, cross-docking), inventory management and logistic network in enterprise.
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Çapar, İsmail. "Coordination of inventory and transportation decisions in a two-stage supply chain." Diss., Mississippi State : Mississippi State University, 2007. http://library.msstate.edu/etd/show.asp?etd=etd-09242007-085706.

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Nečas, Martin. "Řízení průběhu zakázky organizací." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2009. http://www.nusl.cz/ntk/nusl-222026.

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In the Master’s Thesis, the management of processing of an order in the company Pekárny Blansko, a.s., is analyzed. The description of the present way of dealing with the orders is included in the Thesis as well. Subsequently, the Thesis contains a proposal that facilitates meeting the customers’ demands for quantity and time. This solution will contribute to the competitive advantage of the company in the market.
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Song, Jin-Hwa. "Inventory Routing Investigations." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/5028.

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The elimination of distribution inefficiencies, occurring due to the timing of customers' orders is an important reason for companies to introduce vendor managed inventory programs. By managing their customers' inventories, suppliers may be able to reduce demand variability and therefore distribution costs. We develop technology to measure the effectiveness of distribution strategies. We develop a methodology that allows the computation of tight lower bounds on the total mileage required to satisfy customer demand over a period of time. As a result, companies will be able to gain insight into the effectiveness of their distribution strategy. This technology can also be used to suggest desirable delivery patterns and to analyze tactical and strategic decisions. Secondly, we study the inventory routing problem with continuous moves (IRP-CM). The typical inventory routing problem deals with the repeated distribution of a single product, from a single facility, with an unlimited supply, to a set of customers that can all be reached with out-and-back trips. Unfortunately, this is not always the reality. We introduce the IRP-CM to study two important real-life complexities: limited product availabilities at facilities and customers that cannot be served using out-and-back tours. We need to design delivery tours spanning several days, covering huge geographic areas, and involving product pickups at different facilities. We develop a heuristic and an optimization algorithm to construct distribution plans. The heuristic is an innovative randomized greedy algorithm, which includes linear programming based postprocessing technology. To solve the IRP-CM to optimality, we give a time-discretized integer programming model and develop a branch-and-cut algorithm. As instances of time-discretized models tend to be large we discuss several possibilities for reducing the problem size. We introduce a set of valid inequalities, called delivery cover inequalities, in order to tighten the bounds given by the LP relaxation of the time-discretized model. We also introduce branching schemes exploiting the underlying structure of the IRP-CM. An extensive computational study demonstrates the effectiveness of the optimization algorithm. Finally, we present an integrated approach using heuristics and optimization algorithms providing effective and efficient technology for solving inventory problems with continuous moves.
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Ebi-Ndie, Kenneth. "Strategies Used By Logistics Firms To Minimize Costs And Maximize Services : MBA-thesis in marketing." Thesis, University of Gävle, Department of Business Administration and Economics, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-4824.

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Aim: More and more organizations worldwide want to develop products for global markets. At the same time, they need to make their products available in the global market to be competitive. One of today's trends to solve this problem of making products in the global market is by involving logistics to manage complex distribution requirements. Organizations have developed strategic alliances with companies all over the world to manage their logistics operations network. (www.chrobinson.com).

My research was aimed at understanding the coordination of logistics activities at the terminal.

 

Method: I based my study on a combination of descriptive and exploratory type. As regards descriptive I presented my data collected in a descriptive analysis. Also I used the exploratory research to know exactly the implementation of logistics activities at Schenker's terminal and also to observe the activities, conduct interviews and administer questionnaires.

 

Result & Conclusions: The major results of my findings revealed that the existing management procedure of the outbound logistics system at Schenker terminal which involves material handling, transportation, distribution, cross-docking, customer service and information systems could not be seen as lean and agile. This is because of the existence of many problems faced by the terminal such as congestion, flows inefficiencies, excess scrap, too much manual documentation,  delays in deliveries, damages, poor customer service, return goods, idle equipment (forklift and trucks) and personal and high cost of operations.

 

Suggestions for future research: The study is limited in the sense that it does not include the whole supply chain; the terminal is just a part in the supply chain and whatever problems that are encountered are not experienced in the whole supply chain. This could lead to a broader basis of a future research project.

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Yung, King Stanley. "Application of multi-agent technology to supply chain management /." Hong Kong : University of Hong Kong, 1999. http://sunzi.lib.hku.hk/hkuto/record.jsp?B21852170.

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Books on the topic "Inventory and distribution logistics"

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The supply chain in manufacturing, distribution, and transportation: Modeling, optimization, and applications. Boca Raton, FL: CRC Press, 2011.

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Office, General Accounting. Defense Logistics Agency: Process for selecting Defense distribution center site contained weaknesses : report to Congressional requesters. Washington, D.C. (P.O. Box 37050, Washington 20013): The Office, 1998.

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Office, General Accounting. Defense Logistics Agency: Process for selecting defense distribution center site contained weaknesses : report to congressional requesters. Washington, D.C. (P.O. Box 37050, Washington 20013): The Office, 1998.

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1954-, Robbins Marc L., Arroyo Center, Rand Corporation, and United States Army, eds. Leveraging complementary distribution channels for an effective, efficient global supply chain. Santa Monica, CA: RAND, 2007.

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W, Miller L. DRIVE (Distribution and Repair in Variable Environments): Design and operation of the Ogden prototype. Santa Monica, CA: Rand, 1992.

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Fleischmann, Bernhard, and Andreas Klose, eds. Distribution Logistics. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-642-17020-1.

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Illinois. Department of Employment Security. Transportation, distribution & logistics. Springfield, Ill.]: Illinois Dept. of Employment Security, 2007.

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Brandimarte, Paolo. Introduction to distribution logistics. Hoboken, N.J: John Wiley, 2007.

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Nunen, Jo A. E. E., M. Grazia Speranza, and Luca Bertazzi, eds. Innovations in Distribution Logistics. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-92944-4.

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Fleischmann, Bernhard, Jo A. E. E. van Nunen, M. Grazia Speranza, and Paul Stähly, eds. Advances in Distribution Logistics. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-46865-0.

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Book chapters on the topic "Inventory and distribution logistics"

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van der Laan, E. A., M. Salomon, and J. A. A. E. van Nunen. "Reverse logistics and inventory control with product remanufacturing." In Advances in Distribution Logistics, 449–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-46865-0_19.

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Tüshaus, Ulrich, and Christoph Wahl. "Inventory Positioning in a Two-Stage Distribution System with Service Level Constraints." In Advances in Distribution Logistics, 501–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-46865-0_21.

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Agra, Agostinho, Adelaide Cerveira, and Cristina Requejo. "Logistic Operations in a Hospital: A Multi-item Inventory Distribution Problem with Heterogeneous Fleet." In Pharmaceutical Supply Chains - Medicines Shortages, 215–27. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-15398-4_16.

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Ignaciuk, Przemysław, and Łukasz Wieczorek. "Minimum Fuel Resource Distribution in Multidimensional Logistic Networks Governed by Base-Stock Inventory Policy." In Advances in Intelligent Systems and Computing, 1141–51. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-50936-1_95.

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Gudehus, Timm, and Herbert Kotzab. "Inventory Management." In Comprehensive Logistics, 271–327. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24367-7_11.

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Gudehus, Timm, and Herbert Kotzab. "Inventory Management." In Comprehensive Logistics, 271–327. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-68652-1_11.

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Pfohl, Hans-Christian. "Inventory Management (Stockkeeping)." In Logistics Systems, 89–112. Berlin, Heidelberg: Springer Berlin Heidelberg, 2022. http://dx.doi.org/10.1007/978-3-662-64349-5_5.

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Kasilingam, Raja G. "Inventory planning." In Logistics and Transportation, 75–98. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5277-2_5.

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Ignaciuk, Przemysław, and Adam Dziomdziora. "Intelligent Planning of Logistic Networks to Counteract Uncertainty Propagation." In Computational Science – ICCS 2021, 351–64. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77970-2_27.

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AbstractA major obstacle to stable and cost-efficient management of goods distribution systems is the bullwhip effect – reinforced demand uncertainty propagating among system nodes. In this work, by solving a formally established optimization problem, it is shown how one can mitigate the bullwhip effect, at the same minimizing transportation costs, in modern logistic networks with complex topologies. The flow of resources in the analyzed network is governed by the popular order-up-to inventory policy, which thrives to maintain sufficient stock at the nodes to answer a priori unknown, uncertain demand. The optimization objective is to decide how intensive a given transport channel should be used so that unnecessary goods relocation and the bullwhip effect are avoided while being able to fulfill demand requests. The computationally challenging optimization task is solved using a population-based evolutionary technique – Biogeography-Based Optimization. The results are verified in extensive simulations of a real-world transportation network.
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Ross, David Frederick. "Inventory Acquisition." In Distribution, 439–503. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4684-0015-1_10.

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Conference papers on the topic "Inventory and distribution logistics"

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Yang, Haoxiong, Mingke He, and Bin Hu. "Research on Inventory Control for Joint Distribution." In International Conference of Logistics Engineering and Management (ICLEM) 2010. Reston, VA: American Society of Civil Engineers, 2010. http://dx.doi.org/10.1061/41139(387)278.

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Sun, Hui, and Mei Kuang. "Supermarket Multi-Level Inventory and Distribution Optimization Research." In 2014 International Conference of Logistics Engineering and Management. Reston, VA: American Society of Civil Engineers, 2014. http://dx.doi.org/10.1061/9780784413753.006.

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Shui, Wenbing, and Huaizhen Ye. "The Dynamic Relocation of Logistics Distribution Centers with Inventory." In Second International Conference on Transportation Engineering. Reston, VA: American Society of Civil Engineers, 2009. http://dx.doi.org/10.1061/41039(345)141.

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Zhu, Hua. "Zero Inventory Management of Logistics Distribution Based on Network Marketing." In Proceedings of the 4th International Conference on Humanities Science, Management and Education Technology (HSMET 2019). Paris, France: Atlantis Press, 2019. http://dx.doi.org/10.2991/hsmet-19.2019.114.

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Ma, Zujun, Ying Dai, Huajun Li, and Chanchan Wang. "A Fuzzy Location-Routing-Inventory Problem in Logistics Distribution Systems." In Eighth International Conference of Chinese Logistics and Transportation Professionals (ICCLTP). Reston, VA: American Society of Civil Engineers, 2009. http://dx.doi.org/10.1061/40996(330)403.

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Ma, Z. J., and Y. Dai. "A Stochastic Location-Routing-Inventory Problem in Logistics Distribution Systems." In First International Conference on Transportation Engineering. Reston, VA: American Society of Civil Engineers, 2007. http://dx.doi.org/10.1061/40932(246)235.

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Ke, Rong, and Chunrong Ai. "Multi-Stage Inventory Control under Unknown Demand Distribution Function." In Eighth International Conference of Chinese Logistics and Transportation Professionals (ICCLTP). Reston, VA: American Society of Civil Engineers, 2009. http://dx.doi.org/10.1061/40996(330)470.

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Jiang, Sai, Zujun Ma, and Bo Zhang. "A Stochastic Location-Inventory Problem in Refined Oil Distribution Systems." In Eighth International Conference of Chinese Logistics and Transportation Professionals (ICCLTP). Reston, VA: American Society of Civil Engineers, 2009. http://dx.doi.org/10.1061/40996(330)407.

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Huang, Xi, Hui Xiong, An-quan Zou, and Hai-tao Li. "Multi-distribution center inventory demand forecast model in regional logistics network." In EM2010). IEEE, 2010. http://dx.doi.org/10.1109/icieem.2010.5646008.

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Zhang, Bo, Zujun Ma, and Sai Jiang. "Location-Routing-Inventory Problem with Stochastic Demand in Logistics Distribution Systems." In 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). IEEE, 2008. http://dx.doi.org/10.1109/wicom.2008.1547.

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Reports on the topic "Inventory and distribution logistics"

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Figliozzi, Miguel. Distribution Logistics Course. Portland State University Library, August 2009. http://dx.doi.org/10.15760/trec.17.

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Hilburn, Cofield B. Transforming for Distribution Based Logistics. Fort Belvoir, VA: Defense Technical Information Center, May 2005. http://dx.doi.org/10.21236/ada435897.

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Gue, Kevin R. A Dynamic Distribution Model for Combat Logistics. Fort Belvoir, VA: Defense Technical Information Center, November 1999. http://dx.doi.org/10.21236/ada374638.

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Davis, Kevin A. Distribution: Configured Loads as a Logistics Enabler. Fort Belvoir, VA: Defense Technical Information Center, March 2003. http://dx.doi.org/10.21236/ada415122.

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Maddox, David M., and Marygail Brauner. Intra-Theater Logistics Distribution in the CENTCOM AOR. Fort Belvoir, VA: Defense Technical Information Center, October 2004. http://dx.doi.org/10.21236/ada430956.

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Spenard, Thomas M. Force Protection for Distribution Based-Logistics in Asymmetric Warfare. Fort Belvoir, VA: Defense Technical Information Center, May 2005. http://dx.doi.org/10.21236/ada436192.

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Myers, II, and Charles F. Enhanced DLA (Defense Logistics Agency) Distribution System (EDDS) Pooling. Fort Belvoir, VA: Defense Technical Information Center, June 1988. http://dx.doi.org/10.21236/ada201098.

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Mongilutz, Mark J. Force XXI Logistics: Operational Distribution on the Future Battlefield. Fort Belvoir, VA: Defense Technical Information Center, February 1997. http://dx.doi.org/10.21236/ada324811.

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Serne, R. Jeffrey, and Brian M. Rapko. Technetium Inventory, Distribution, and Speciation in Hanford Tanks. Office of Scientific and Technical Information (OSTI), May 2014. http://dx.doi.org/10.2172/1130665.

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Serne, R. Jeffrey, Brian M. Rapko, and Ian L. Pegg. Technetium Inventory, Distribution, and Speciation in Hanford Tanks. Office of Scientific and Technical Information (OSTI), November 2014. http://dx.doi.org/10.2172/1184302.

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