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Artículos de revistas sobre el tema "Event-Chain"

Autor: Grafiati

Publicado: 30 de noviembre de 2024

Última modificación: 31 de julio de 2025

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1

Heusler, Klaus Felix, Wolfgang Stölzle, and Harald Bachmann. "Supply Chain Event Management." WiSt - Wirtschaftswissenschaftliches Studium 35, no. 1 (2006): 19–24. http://dx.doi.org/10.15358/0340-1650-2006-1-19.

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2

Nissen, Volker. "Supply Chain Event Management." Wirtschaftsinformatik 44, no. 5 (2002): 477–80. http://dx.doi.org/10.1007/bf03250869.

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3

Sangeetha, S., R. S. Thakur, and Michael Arock. "Event detection using trigger chain." International Journal of Knowledge Engineering and Data Mining 2, no. 1 (2012): 76. http://dx.doi.org/10.1504/ijkedm.2012.044708.

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4

Barclay, Lorna M., Rodrigo A. Collazo, Jim Q. Smith, Peter A. Thwaites, and Ann E. Nicholson. "The dynamic chain event graph." Electronic Journal of Statistics 9, no. 2 (2015): 2130–69. http://dx.doi.org/10.1214/15-ejs1068.

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5

Gautham, Ram Rajendiran. "Event Handler Platform for Large-Scale Supply Chain Systems." European Journal of Advances in Engineering and Technology 8, no. 5 (2021): 53–58. https://doi.org/10.5281/zenodo.13919505.

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In large-scale supply chain systems that are built with the service oriented architecture pattern [1], event handling plays a critical role in managing operations like inventory updates, order processing and logistics [3]. However, inconsistent event-handling mechanisms across teams dedicated to managing such a large scale system can lead to a lack of holistic view of events that enable proactive identification of supply chain risks [4] in the system and redundant development work to handle events. This paper proposes a centralized event-handling platform that standardizes interfaces, provides

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6

Lv, Shangwen, Wanhui Qian, Longtao Huang, Jizhong Han, and Songlin Hu. "SAM-Net: Integrating Event-Level and Chain-Level Attentions to Predict What Happens Next." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 6802–9. http://dx.doi.org/10.1609/aaai.v33i01.33016802.

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Scripts represent knowledge of event sequences that can help text understanding. Script event prediction requires to measure the relation between an existing chain and the subsequent event. The dominant approaches either focus on the effects of individual events, or the influence of the chain sequence. However, only considering individual events will lose much semantic relations within the event chain, and only considering the sequence of the chain will introduce much noise. With our observations, both the individual events and the event segments within the chain can facilitate the prediction

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7

Stölzle, Wolfgang. "Kommentar zum Supply Chain Event Management." Die Unternehmung 65, no. 2 (2011): 130–32. http://dx.doi.org/10.5771/0042-059x-2011-2-130.

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8

Otto, Andreas. "Supply Chain Event Management: Three Perspectives." International Journal of Logistics Management 14, no. 2 (2003): 1–13. http://dx.doi.org/10.1108/09574090310806567.

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Supply Chain Event Management (SCEM) addresses a fundamental business problem: inter‐organizational processes rarely execute as scheduled, since they happen in an environment prone to failure and disturbance. SCEM attempts to identify, as early as possible, the resulting deviations between the plan and its execution across the multitude of processes and actors in the supply chain to trigger corrective actions according to predefined rules. Despite SCEM's well documented attractiveness for practitioners, it has received little attention as a field of academic research. This paper provides an in

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9

Barclay, Lorna M., Jane L. Hutton, and Jim Q. Smith. "Chain Event Graphs for Informed Missingness." Bayesian Analysis 9, no. 1 (2014): 53–76. http://dx.doi.org/10.1214/13-ba843.

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10

Smith, Jim Q., and Paul E. Anderson. "Conditional independence and chain event graphs." Artificial Intelligence 172, no. 1 (2008): 42–68. http://dx.doi.org/10.1016/j.artint.2007.05.004.

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11

Thwaites, Peter, Jim Q. Smith, and Eva Riccomagno. "Causal analysis with Chain Event Graphs." Artificial Intelligence 174, no. 12-13 (2010): 889–909. http://dx.doi.org/10.1016/j.artint.2010.05.004.

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12

Thwaites, Peter. "Causal identifiability via Chain Event Graphs." Artificial Intelligence 195 (February 2013): 291–315. http://dx.doi.org/10.1016/j.artint.2012.09.003.

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13

Rinab, Peter. "RFID im mobile supply chain event management." WIRTSCHAFTSINFORMATIK 49, no. 4 (2007): 312. http://dx.doi.org/10.1007/s11576-007-0123-5.

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14

HUANG, Z. Y. "DYNAMIC PROGRAMMING PATH OF MOBILE ROBOT BASED ON EVENT-DRIVEN PROCESS." Latin American Applied Research - An international journal 48, no. 4 (2018): 317–22. http://dx.doi.org/10.52292/j.laar.2018.247.

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Event-driven process chain is an important method for path flow and system optimization in the process of robot dynamic planning path research. Path planning is an important part of robot research. The path planning problem and the path optimization planning problem of the robot in the dynamic environment are explored deeply in this paper based on the event-driven process chain perspective and the actual needs of the research project. Therefore, it uses the event-driven process chain method to optimize the path according to the original process and existing requirements based on the concept of

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15

Banno, H., D. Mugita, and M. Isobe. "Diffusional characteristics of a Newtonian event-chain Monte Carlo in hard disk systems." Journal of Physics: Conference Series 2207, no. 1 (2022): 012011. http://dx.doi.org/10.1088/1742-6596/2207/1/012011.

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Abstract The equilibration and relaxation times of the physical properties of time correlation functions have historically been of fundamental importance in terms of molecular simulation. An efficient algorithm for the acceleration of equilibration, termed the ‘event-chain Monte Carlo’ has been investigated over the past decade. Recently, by adding the collision rule often used in event-driven molecular dynamics, a Newtonian event-chain Monte Carlo was developed. In this event-chain Monte Carlo and variants thereof, optimal performance strongly depends on chain length, physical properties, and

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16

Bodendorf, Freimut, and Roland Zimmermann. "Proactive Supply-Chain Event Management with Agent Technology." International Journal of Electronic Commerce 9, no. 4 (2005): 58–89. http://dx.doi.org/10.1080/10864415.2003.11044340.

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17

Freeman, G., and J. Q. Smith. "Bayesian MAP model selection of chain event graphs." Journal of Multivariate Analysis 102, no. 7 (2011): 1152–65. http://dx.doi.org/10.1016/j.jmva.2011.03.008.

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18

Vlahakis, George, Dimitris Apostolou, and Evi Kopanaki. "Enabling situation awareness with supply chain event management." Expert Systems with Applications 93 (March 2018): 86–103. http://dx.doi.org/10.1016/j.eswa.2017.10.013.

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19

Karlsson, Ulf, and Anders Ulfvarson. "Chain Breakers—A Survey of Fatal Ship Accidents With the Event-Chain Method." Marine Technology and SNAME News 45, no. 03 (2008): 182–90. http://dx.doi.org/10.5957/mt1.2008.45.3.182.

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The ship research project DESSO (Design for Survival Onboard) aims at improving the safety of RO/RO (roll-on/roll-off) ferries. The project was organized in the autumn of 2003 in order to use the research and development resources existing in Sweden, combined with international expertise, for a radical RO/RO concept with a focus on safety. One part in the early stages of this project was to identify chain breakers from previous accidents, that is, something that would have prevented, stopped, or reduced the conse-quences of the incident event, in order to obtain a realistic basis of "working o

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20

Cigolini, Roberto, Margherita Pero, Tommaso Rossi, and Andrea Sianesi. "Linking supply chain configuration to supply chain perfrmance: A discrete event simulation model." Simulation Modelling Practice and Theory 40 (January 2014): 1–11. http://dx.doi.org/10.1016/j.simpat.2013.08.002.

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21

Yoo, Joanne Jung-Eun, and Meehee Cho. "Supply chain flexibility fit and green practices: evidence from the event industry." International Journal of Contemporary Hospitality Management 33, no. 7 (2021): 2410–27. http://dx.doi.org/10.1108/ijchm-09-2020-0999.

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Purpose As the event industry is supported by a wide range of suppliers that provide different products and services, all these partners in the supply chain can play a crucial role in green practices. The industry needs to have a sufficient degree of supply chain flexibility to cater to the demands in today’s dynamic environment and the flexibility in the supply chain will help event businesses to be sustainable. This study aims to explore the role of the supply chain flexibility fit between event planner’s requirements and supplier offerings on the implementation of green practices. The study

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22

Fu, Bin Bin, and Jie Zhu. "A Research on Complex Event Processing Technology Based on Smart Logistic System." Applied Mechanics and Materials 722 (December 2014): 430–35. http://dx.doi.org/10.4028/www.scientific.net/amm.722.430.

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With IOT technology developing and the cost reducing, Its application in supply chain is a matter of time. Smart logistic system is one of the IOT technology application in supply chain which solve difficult problems, such as acquisition underlying data, information transfer and so on. we need to achieve higher level application and solve more complex problems such as improving inventory management accuracy, reducing supply chain management cost, improving accuracy of supply and demand prediction, supply chain's rapidly react ability,these need to use complex event processing technology. It wi

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23

Vasthu, Durango. "Global Supply Chain Management Conference." International Journal of Risk and Contingency Management 1, no. 1 (2012): 64–65. http://dx.doi.org/10.4018/ijrcm.2012010105.

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The 2011 annual ‘big event’ in the global supply chain industry was held in Philadelphia PA USA during the week of October 2-5. This event is organized each year, and is the official global meeting, for the Council of Supply Chain Management Professionals (CSCMP, http://cscmp.org/events/annual-global/sessionsearch-after.asp). The conference featured risk-related topics ranging from inventory forecasting to reverse logistics planning in globally-impacted markets.

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24

Shi, Min, and Wei Yu. "Market Reactions to Supply Chain Management Excellence." Journal of Risk and Financial Management 11, no. 4 (2018): 62. http://dx.doi.org/10.3390/jrfm11040062.

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A highly-respected public recognition of supply chain management (SCM) excellence is the Supply Chain Top 25 List, published annually by AMR Research. By employing event study method, this study extensively examined stock market reactions to annual announcements of the AMR Supply Chain Top 25 List, under various market scenarios. The results showed that SCM leading firms consistently outperform market portfolios around annual press-release dates. The mean abnormal returns observed in the event window (0, +1) were positive and statistically significant. In addition, the findings were robust acr

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25

Lee, Chung-Hong, Hsin-Chang Yang, Yu-Chen Wei, and Wen-Kai Hsu. "Enabling Blockchain Based SCM Systems with a Real Time Event Monitoring Function for Preemptive Risk Management." Applied Sciences 11, no. 11 (2021): 4811. http://dx.doi.org/10.3390/app11114811.

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The risk of supply chain disruption is usually related to daily disturbances in supply chain operations (e.g., demand fluctuations) and some emergency risks, such as earthquakes and epidemic outbreaks. During a crisis, companies need agility to quickly find new suppliers and open auxiliary sales channels to meet customer needs and remain competitive. However, identifying “event” is one of the most difficult challenges of current decision support systems. If the system encounters an emergency, it is usually unable to promptly notify users of the warning to avoid risks. A sensible solution is to

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26

Wang, Q. "A discrete event modelling approach for supply chain simulation." International Journal of Simulation Modelling 7, no. 3 (2008): 124–34. http://dx.doi.org/10.2507/ijsimm07(3)2.100.

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27

Avlijaš, Goran, and Miljan Radunović. "Application of Event Chain Methodology in Schedule Risk Analysis." European Project Management Journal 9, no. 2 (2019): 26–34. http://dx.doi.org/10.18485/epmj.2019.9.2.3.

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28

Jain, Swati, Suraj Prakash Narayan, Nalini Meena, et al. "Event Detection through Lexical Chain Based Semantic Similarity Algorithm." IOP Conference Series: Materials Science and Engineering 1166, no. 1 (2021): 012016. http://dx.doi.org/10.1088/1757-899x/1166/1/012016.

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29

Wahyuni, H. C., I. Vanany, and U. Ciptomulyono. "Identifying risk event in Indonesian fresh meat supply chain." IOP Conference Series: Materials Science and Engineering 337 (April 2018): 012031. http://dx.doi.org/10.1088/1757-899x/337/1/012031.

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30

Doronina, Victoria A., Pablo de Felipe, Cheng Wu, et al. "Dissection of a co-translational nascent chain separation event." Biochemical Society Transactions 36, no. 4 (2008): 712–16. http://dx.doi.org/10.1042/bst0360712.

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Some RNA and protein sequences are capable of directing changes to the course of translation from that expected from the mRNA sequence, and this process is termed translational ‘recoding’. ‘CHYSEL’ peptides are ∼19-amino-acid sequences found in many viral genomes. When translated at internal portions of polypeptides, they yield co-translational separation of the nascent chain at their C-termini. We dissected the reaction promoted by CHYSEL sequences using yeast genetics and in vitro translation systems. Our results indicate that the reaction occurs within the peptidyltransferase centre of the

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31

Barclay, L. M., J. L. Hutton, and J. Q. Smith. "Refining a Bayesian Network using a Chain Event Graph." International Journal of Approximate Reasoning 54, no. 9 (2013): 1300–1309. http://dx.doi.org/10.1016/j.ijar.2013.05.006.

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32

Palma, Fanny, Jania A. Saucedo, J. A. Marmolejo-Saucedo, and Roman Rodriguez-Aguilar. "The supply chain event management application: a case study." IFAC-PapersOnLine 52, no. 13 (2019): 2698–703. http://dx.doi.org/10.1016/j.ifacol.2019.11.615.

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33

Darrall, Jan. "1992: a non-event? Perceptions of the food chain." Food Policy 17, no. 1 (1992): 81–83. http://dx.doi.org/10.1016/0306-9192(92)90020-x.

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34

Michel, Manon, Johannes Mayer, and Werner Krauth. "Event-chain Monte Carlo for classical continuous spin models." EPL (Europhysics Letters) 112, no. 2 (2015): 20003. http://dx.doi.org/10.1209/0295-5075/112/20003.

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35

Sangjin Lee, Weiyi Liu, and Inseok Hwang. "Markov Chain Approximation Algorithm for Event-Based State Estimation." IEEE Transactions on Control Systems Technology 23, no. 3 (2015): 1123–30. http://dx.doi.org/10.1109/tcst.2014.2349971.

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36

Echefaj, K., A. Charkaoui, and A. Cherrafi. "Analyzing Capabilities for Resilient Supply Chain in Unexpected Event." IFAC-PapersOnLine 55, no. 10 (2022): 3190–95. http://dx.doi.org/10.1016/j.ifacol.2022.10.220.

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37

Liu, Rong, Akhil Kumar, and Wil van der Aalst. "A formal modeling approach for supply chain event management." Decision Support Systems 43, no. 3 (2007): 761–78. http://dx.doi.org/10.1016/j.dss.2006.12.009.

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38

Zhao, Lijuan, Yi Li, Shihua Luo, et al. "Choroid Theory Guides the Theory of Cardiovascular Event Chain." Highlights in Science, Engineering and Technology 30 (February 15, 2023): 196–200. http://dx.doi.org/10.54097/hset.v30i.4973.

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The theory, cardiovascular disease is one of the most common clinical chronic diseases. Modern medicine has confirmed that cardiovascular diseases are caused by the long-term accumulation and deposition of various pathological products caused by a variety of causes, and most of them are non-specific. Cardiovascular events such as acute myocardial infarction and stroke mainly occur in the occurrence process of cardiovascular diseases and cerebrovascular accidents, so the pathogenesis of cardiovascular and cerebrovascular diseases is very complex and difficult to predict. Therefore, this paper c

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39

Devaraju, Sudheer, and Srikanth Katta. "Real-Time Integration Monitoring in Workday for Global Retailers Using Event-Driven Architecture." Real-Time Integration Monitoring in Workday for Global Retailers Using Event-Driven Architecture 7, no. 6 (2020): 101–6. https://doi.org/10.5281/zenodo.14296530.

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<strong>ABSTRACT</strong> Global enterprises such as Walmart use Workday to harmonize staffing and vendor management activities, and to integrate supply chain activities. Failures of such integrations can result in operational inefficiencies and financial losses, and even ruin critical workflows. In this paper we have developed an EDA for Workday integration event monitoring using Java Message Service (JMS) and RabbitMQ. The construction of predictive dashboards and proactive alerts is proposed to be integrated with Core Connector and Enterprise Interface Builder (EIB). A case study with a mul

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40

Malyshev, E., and T. Malysheva. "THE USE OF DIGITAL TECHNOLOGY IN SUPPLY CHAIN MANAGEMENT." Transbaikal state university journal 27, no. 3 (2021): 113–18. http://dx.doi.org/10.21209/2227-9245-2021-27-3-113-118.

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This article provides an overview of the event management concept in supply chains. The management of organizational change in supply chains can be based on five basic approaches. Supply Chain Event Management is the creation and management of supply chain events. The concept of SCEM involves tracing objects, which are defined as reference points, across multiple events. SCEM is an integration of the following aspects: monitoring; notification; modelling; control; measurement. The study shows that this system is beneficial for supply chain management

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41

Li, Jun Tao, Gang Lin, and Xiao Lin Cheng. "Research of IOT Context-Aware Processing Framework Based on Complex Event for Supply Chain Application." Applied Mechanics and Materials 263-266 (December 2012): 1677–87. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.1677.

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In order to solve the logic fault of Internet of things technology applied in the supply chain system, this paper presents a supply chain oriented context-aware Framework which is based on Complex Event Processing. The frame is subdivided into five levels and proposes an active event flow situation model based on Complex Event Processing. Besides, it can provide a semantic senior situation for the application of the upper layer through processing the uncertainty contextual information under the semantic rules, as a support for the top decision.

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42

Fan, Min, and Shanwen Xu. "Research on Discourse Coherence based on the Analysis Model of Event Chain from the Perspective of Computational Linguistics." E3S Web of Conferences 189 (2020): 03025. http://dx.doi.org/10.1051/e3sconf/202018903025.

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With the rapid development of network technology, natural language processing has also entered a boom period. Probability and data-driven methods have been widely used in natural language processing. The need for people to extract and retrieve information from the Internet is also increasing, and more and more researchers are trying to use computers to process content related to discourse coherence. Based on the event chain of the text semantic structure representation, this paper proposes a text semantic structure representation model, on the basis of which, text coherent resources can be use

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43

Al-Fedhly, Haider, and Duncan Folley. "Discrete Event Simulation Software for Agent-Based Supply Chain Demand." International Journal of Industry and Sustainable Development 1, no. 2 (2020): 20–35. http://dx.doi.org/10.21608/ijisd.2020.101606.

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44

Kang, Jun-Gyu, and Seung-Kil Lim. "Business Process Analysis Based on Event-driven Process Chain Model." Journal of Society of Korea Industrial and Systems Engineering 36, no. 3 (2013): 34–42. http://dx.doi.org/10.11627/jkise.2013.36.3.34.

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45

Jankowska, Anna Maria, Karl Kurbel, and Denny Schreber. "An architecture for agent-based mobile Supply Chain Event Management." International Journal of Mobile Communications 5, no. 3 (2007): 243. http://dx.doi.org/10.1504/ijmc.2007.012393.

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46

Yoo, Taejong, Hyunbo Cho, and Enver Yücesan. "Hybrid algorithm for discrete event simulation based supply chain optimization." Expert Systems with Applications 37, no. 3 (2010): 2354–61. http://dx.doi.org/10.1016/j.eswa.2009.07.039.

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47

Cowell, Robert G., and James Q. Smith. "Causal discovery through MAP selection of stratified chain event graphs." Electronic Journal of Statistics 8, no. 1 (2014): 965–97. http://dx.doi.org/10.1214/14-ejs917.

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48

Isobe, Masaharu, and Werner Krauth. "Hard-sphere melting and crystallization with event-chain Monte Carlo." Journal of Chemical Physics 143, no. 8 (2015): 084509. http://dx.doi.org/10.1063/1.4929529.

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49

Achee, Badrul, Saikat Kundu, and Muhammad Latif. "Exploiting Discrete Event Simulation to Improve a Chicken Supply Chain." BOHR International Journal of Advances in Management Research 1, no. 1 (2022): 65–75. http://dx.doi.org/10.54646/bijamr.008.

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This article focuses on improving supply chain management (SCM) at a poultry processing plant. The strategies applied in SCM are dependent on understanding customers’ demand, the ability to forecast accurately, and maintaining smart inventory management to achieve the full advantages of SCM. This study exploits the integration of SCM concepts with business simulation, along with exploring strategies to improve the whole operation of a chicken supply chain. Witness Horizon software is utilized to model the supply chain of Company X, and information gathered on the demand and sales of poultry (c

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50

Bearzotti, Lorena A., Enrique Salomone, and Omar J. Chiotti. "An autonomous multi-agent approach to supply chain event management." International Journal of Production Economics 135, no. 1 (2012): 468–78. http://dx.doi.org/10.1016/j.ijpe.2011.08.023.

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