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Journal articles on the topic 'Dynamic Routing Systems'

Author: Grafiati

Published: 7 June 2025

Last updated: 11 July 2025

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1

Bullo, F., E. Frazzoli, M. Pavone, K. Savla, and S. L. Smith. "Dynamic Vehicle Routing for Robotic Systems." Proceedings of the IEEE 99, no. 9 (2011): 1482–504. http://dx.doi.org/10.1109/jproc.2011.2158181.

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2

Zhai, Xin. "Benefits of Dynamic Routing in a Distribution System with Single Warehouse and Multiple Retailers." International Journal of Information Systems and Supply Chain Management 5, no. 3 (2012): 24–42. http://dx.doi.org/10.4018/jisscm.2012070102.

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The author investigates a distribution system consisting of one warehouse and multiple retailers. First, they study the characteristics of a dynamic allocation policy associated with dynamic routing policy. The authors, then, conduct simulation study to investigate the performance of different forms of dynamic routing policies under both symmetric and asymmetric scenarios. The author’s numerical findings show that both SLIF (Static Least Inventory First) routing and DLIF (Dynamic Least Inventory First) routing outperform static routing significantly. In addition, DLIF routing provides more savings compared to SLIF routing. When the asymmetry among retailers is not significant, both SLIF routing and DLIF routing can be used as good heuristic dynamic routing policies given that they are easy to execute.

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3

LIM, Jae Kook, Kap Hwan KIM, Ki Young KIM, Teruo TAKAHASHI, and Kazuho YOSHIMOTO. "Dynamic Routing in Automated Guided Vehicle Systems." JSME International Journal Series C 45, no. 1 (2002): 323–32. http://dx.doi.org/10.1299/jsmec.45.323.

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4

Yu, P. S., S. Balsamo, and Y. H. Lee. "Dynamic transaction routing in distributed database systems." IEEE Transactions on Software Engineering 14, no. 9 (1988): 1307–18. http://dx.doi.org/10.1109/32.6174.

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5

Maimon, Oded Z., and Yong F. Choong. "Dynamic routing in reentrant flexible manufacturing systems." Robotics and Computer-Integrated Manufacturing 3, no. 3 (1987): 295–300. http://dx.doi.org/10.1016/0736-5845(87)90036-6.

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6

Zhu, Ning, Yang Liu, Shoufeng Ma, and Zhengbing He. "Mobile Traffic Sensor Routing in Dynamic Transportation Systems." IEEE Transactions on Intelligent Transportation Systems 15, no. 5 (2014): 2273–85. http://dx.doi.org/10.1109/tits.2014.2314732.

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7

Demeyer, Sofie, Mario Pickavet, Piet Demeester, and Pieter Audenaert. "Dynamic and stochastic routing for multimodal transportation systems." IET Intelligent Transport Systems 8, no. 2 (2014): 112–23. http://dx.doi.org/10.1049/iet-its.2012.0065.

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8

Uncu, Nuşin, and Rızvan Erol. "Capacity Optimization in Dynamically Routing Computer Network Systems." Tehnički glasnik 16, no. 1 (2022): 23–32. http://dx.doi.org/10.31803//tg-20201215233216.

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A computer network system is a complex system with a great number of dynamic components. There are many devices in the system, such as computers, routers, lines, hubs, and switches. In addition to these hardware systems, many protocols are integrated to set the rules and provide the way of communication. Due to the nature of the system, it is hard to formulate and solve problems analytically without making any assumptions. One of the prominent problems that occur in computer systems is the line capacity assignment problem. In the previous mathematical models, message routes were predetermined and the dynamic nature of the system was neglected. This study deals with the line capacity assignment problem under a dynamically routing policy. Four different computer network topologies are used and solved by two heuristic algorithms via simulation. A dynamic search approach based on the occupancy rate of lines is used to define the consecutive routes of messages. The performances of harmony search and genetic algorithms via simulation are compared with the results of OptQuest, one of the optimization packet programs embedded in simulation software Arena®.

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9

Armony, Mor, and Amy R. Ward. "Fair Dynamic Routing in Large-Scale Heterogeneous-Server Systems." Operations Research 58, no. 3 (2010): 624–37. http://dx.doi.org/10.1287/opre.1090.0777.

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10

Kargahi, Mehdi, and Ali Movaghar. "Utility Accrual Dynamic Routing in Real-Time Parallel Systems." IEEE Transactions on Parallel and Distributed Systems 21, no. 12 (2010): 1822–35. http://dx.doi.org/10.1109/tpds.2010.50.

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11

Bartlett, Kelly, Junho Lee, Shabbir Ahmed, George Nemhauser, Joel Sokol, and Byungsoo Na. "Congestion-aware dynamic routing in automated material handling systems." Computers & Industrial Engineering 70 (April 2014): 176–82. http://dx.doi.org/10.1016/j.cie.2014.02.002.

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12

Kumar, Akhil, and J. Leon Zhao. "Dynamic Routing and Operational Controls in Workflow Management Systems." Management Science 45, no. 2 (1999): 253–72. http://dx.doi.org/10.1287/mnsc.45.2.253.

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13

Smolic-Rocak, N., S. Bogdan, Z. Kovacic, and T. Petrovic. "Time Windows Based Dynamic Routing in Multi-AGV Systems." IEEE Transactions on Automation Science and Engineering 7, no. 1 (2010): 151–55. http://dx.doi.org/10.1109/tase.2009.2016350.

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14

Brinkmann, Jan, Marlin W. Ulmer, and Dirk C. Mattfeld. "Dynamic Lookahead Policies for Stochastic-Dynamic Inventory Routing in Bike Sharing Systems." Computers & Operations Research 106 (June 2019): 260–79. http://dx.doi.org/10.1016/j.cor.2018.06.004.

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15

Windmann, Stefan, Kaja Balzereit, and Oliver Niggemann. "Model-based routing in flexible manufacturing systems." at - Automatisierungstechnik 67, no. 2 (2019): 95–112. http://dx.doi.org/10.1515/auto-2018-0108.

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Abstract In this paper, a model-based routing approach for flexible manufacturing systems (FMS) with alternative routes for the work pieces is proposed. For each work piece, an individual task has to be accomplished, which consists of several processing steps. Each processing step can be executed on alternative working stations of the FMS. The proposed routing method employs a model of the conveying system to find energy efficient and fast routes for the respective work pieces. The conveying system model is based on a directed graph, where the individual conveyors are modeled as weighted edges. It can be straightforwardly applied to several types of FMS by adjusting the application-dependent parameters. Efficient computation of the fastest route through the conveying system is accomplished by means of dynamic programming, i. e., by integration of Dijkstra’s algorithm in a dynamic programming framework, which is based on the proposed conveying system model. Additional consideration of energy efficiency aspects leads to a Mixed Integer Quadratically Constraint Program (MIQCP), which is solved by substitution of Dijkstra’s algorithm by a branch and bound method. Experimental results for an application scenario, where the energy efficient routing method is applied to route work pieces between the working stations of an FMS, lead to 20 % reduction of energy consumption on average.

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16

Gupta, Kavyansh. "D.R.O.N.E : Dynamic Routing for Optimal Navigation and Evasion." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 12 (2024): 1–8. https://doi.org/10.55041/ijsrem40159.

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D.R.O.N.E. represents more than merely a navigation system; it is an advanced algorithmic framework (in fact) designed to transform the way airborne vehicles engage with their surroundings. Consider it the quintessential flight assistant, endowed with real-time data processing capabilities that—arguably—compete with the most cutting-edge AI systems. However, this technology is not without its challenges. Although there are significant advancements being made, the complexities of integrating such systems into existing infrastructures remain a hurdle. Because of this, ongoing research and development are imperative to ensure its successful implementation.

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17

Rossi, Roberto, Maurizio Tomasella, Belen Martin-Barragan, Tim Embley, Christopher Walsh, and Matthew Langston. "The Dynamic Bowser Routing Problem." European Journal of Operational Research 275, no. 1 (2019): 108–26. http://dx.doi.org/10.1016/j.ejor.2018.11.026.

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18

Wu, Qing, Qing-Yang Liu, Xiang Ling, and Li-Jun Zhang. "The self-adaptive routing strategy to alleviate packet loss in finite buffer networks." Journal of Statistical Mechanics: Theory and Experiment 2021, no. 12 (2021): 123402. http://dx.doi.org/10.1088/1742-5468/ac3b44.

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Abstract In real communication or transportation systems, loss of agents is very common due to finite storage capacity. We study the traffic dynamics in finite buffer networks and propose a routing strategy motivated by a heuristic algorithm to alleviate packet loss. Under this routing strategy, the traffic capacity is further improved, comparing to the shortest path routing strategy and efficient routing strategy. Then we investigate the effect of this routing strategy on the betweenness of nodes. Through dynamic routing changes, the maximum node betweenness of the network is greatly reduced, and the final betweenness of each node is almost the same. Therefore, the routing strategy proposed in this paper can balance the node load, thereby effectively alleviating packet loss.

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19

PAVLIKOV, SERGEJ N., EVGENIA A. ZIMAREVA, MILENA D. BOGDAN, and ALENA S. CEPELEVA. "MULTIDIMENSIONAL DYNAMIC ROUTING METHOD IN RADIO NETWORK." H&ES Research 13, no. 2 (2021): 16–24. http://dx.doi.org/10.36724/2409-5419-2021-13-2-16-24.

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Introduction: The introduction of information technology has accelerated the development of methods to improve communication systems. The aim of the study is to improve the efficiency of the network with batch data transmission. Methods: achieving the goal is carried out in three stages, the first stage is considered the task of expanding the functions of repeaters, the second — the functions of the relay are combined with the functions of the switch, and then considered the possibility of obtaining a super-sumar effect through the system use of the repeater-switch-converter. Results: spatial coding of message delivery tracks through real and virtual repeaters allows you to expand the many routes through which, according to the specified criteria, packages are transferred, in the points of space agreed by subscribers is the formation of packages in enlarged groups, transformation by separation methods and spatial switching to the following switching points. The process of forming a spatial field of relay points and visualization of the separation of routes of radio transmissions was carried out. Practical significance: the formation of multiple signals at the focus points implements transformation processes, and the joint processing of processes at multiple relay points provides a switching through the space, for example, for the coordinate space, the lighting of the area of uncertain reception. Discussion: The implementation of a new set of resource management principles in the delivery of communication creates conditions for a significant increase in the simultaneous use of information technologies in a unit of space, allowing for the implementation of a new approach, which is to combine the processes of separation and cooperation of the means of information exchange into self-organizing systems, to jointly perform an expanded range of tasks.

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20

Nguyen, Ho Si Hung, Phuc Do, Hai-Canh Vu, and Benoit Iung. "Dynamic maintenance grouping and routing for geographically dispersed production systems." Reliability Engineering & System Safety 185 (May 2019): 392–404. http://dx.doi.org/10.1016/j.ress.2018.12.031.

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21

Roszkowska, Elzbieta. "Supervisory control for closed agv systems with dynamic vehicle routing." IFAC Proceedings Volumes 36, no. 17 (2003): 413–18. http://dx.doi.org/10.1016/s1474-6670(17)33429-8.

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22

Armony, Mor. "Dynamic Routing in Large-Scale Service Systems with Heterogeneous Servers." Queueing Systems 51, no. 3-4 (2005): 287–329. http://dx.doi.org/10.1007/s11134-005-3760-7.

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23

Seidmann, Abraham. "Optimal dynamic routing in Flexible Manufacturing Systems with limited buffers." Annals of Operations Research 15, no. 1 (1988): 289–311. http://dx.doi.org/10.1007/bf02186800.

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24

Kang, Bonggwon, Byeong Min Kang, and Soondo Hong. "A Dynamic OHT Routing Algorithm in Automated Material Handling Systems." Journal of Society of Korea Industrial and Systems Engineering 45, no. 3 (2022): 40–48. http://dx.doi.org/10.11627/jksie.2022.45.3.040.

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25

Tapolcai, Janos, and Pin-Han Ho. "Dynamic survivable routing for shared segment protection." Journal of Communications and Networks 9, no. 2 (2007): 198–209. http://dx.doi.org/10.1109/jcn.2007.6182840.

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26

Huang, Guanyao, Chen-Nee Chuah, Saqib Raza, and Srini Seetharaman. "Dynamic measurement-aware routing in practice." IEEE Network 25, no. 3 (2011): 29–34. http://dx.doi.org/10.1109/mnet.2011.5772058.

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27

Peltsverger, Svetlana. "Dynamic structured routing in mobile networks." International Journal of Mobile Network Design and Innovation 2, no. 2 (2007): 134. http://dx.doi.org/10.1504/ijmndi.2007.015064.

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28

AHMED, N. U., T. E. DABBOUS, and Y. W. LEE. "Dynamic routing for computer queueing networks." International Journal of Systems Science 19, no. 6 (1988): 967–77. http://dx.doi.org/10.1080/00207728808547178.

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29

Xu, Xiao-Lan, Wen-Bo Du, and Chen Hong. "Cascade defense via routing in complex networks." International Journal of Modern Physics C 26, no. 12 (2015): 1550141. http://dx.doi.org/10.1142/s0129183115501417.

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As the cascading failures in networked traffic systems are becoming more and more serious, research on cascade defense in complex networks has become a hotspot in recent years. In this paper, we propose a traffic-based cascading failure model, in which each packet in the network has its own source and destination. When cascade is triggered, packets will be redistributed according to a given routing strategy. Here, a global hybrid (GH) routing strategy, which uses the dynamic information of the queue length and the static information of nodes' degree, is proposed to defense the network cascade. Comparing GH strategy with the shortest path (SP) routing, efficient routing (ER) and global dynamic (GD) routing strategies, we found that GH strategy is more effective than other routing strategies in improving the network robustness against cascading failures. Our work provides insight into the robustness of networked traffic systems.

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30

Amaresha Prasad Sahoo. "Dynamic routing algorithms in customer support: Revolutionizing contact center operations." World Journal of Advanced Engineering Technology and Sciences 15, no. 2 (2025): 2976–83. https://doi.org/10.30574/wjaets.2025.15.2.0880.

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Dynamic routing algorithms have transformed contact center operations through AI-driven decision-making and real-time data analytics. These systems optimize customer-agent matching while enhancing operational efficiency through intelligent queue management and predictive analytics. The integration of machine learning, natural language processing, and sentiment analysis capabilities has revolutionized how contact centers handle customer interactions, leading to improved resolution rates and customer satisfaction. Cloud-native solutions and emerging technologies continue to advance routing capabilities, offering scalable and adaptable systems that respond to changing customer needs and business requirements. The sophisticated architecture of these systems incorporates multiple layers of data processing and decision intelligence, enabling real-time adaptation to changing interaction patterns and customer preferences. Advanced analytics components process vast amounts of historical and real-time data to create comprehensive customer profiles and interaction histories, facilitating more precise routing decisions. The implementation of dynamic routing algorithms has demonstrated significant improvements across key performance indicators, including reduced handling times, improved first-contact resolution rates, and enhanced customer experience metrics. Furthermore, the integration of artificial intelligence and machine learning continues to push the boundaries of routing sophistication, enabling more nuanced understanding of customer intent and emotional states, while cloud-based infrastructure ensures scalability and reliability across diverse operational environments.

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31

Rismanto, Hilman, and Loso Judijanto. "Dynamic Routing in Urban Logistics: A Comprehensive Review of AI, Real-Time Data, and Sustainability Impacts." Sinergi International Journal of Logistics 3, no. 2 (2025): 68–79. https://doi.org/10.61194/sijl.v3i2.741.

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This paper examines the impact of dynamic routing algorithms on urban logistics, focusing on their role in improving operational efficiency and environmental sustainability. With the rise of e-commerce and the increasing complexity of urban transport networks, dynamic routing has emerged as a critical solution for reducing delivery times, optimizing fleet usage, and minimizing emissions. The methodology for this review involved a comprehensive search of key academic databases, including Scopus, IEEE Xplore, and Google Scholar, using relevant keywords and inclusion criteria. The results demonstrate that algorithms integrating real-time data, artificial intelligence, and hybrid optimization models significantly enhance routing decisions. Furthermore, real-time systems that incorporate GIS and IoT data enable more responsive and context-aware logistics operations. However, challenges such as infrastructure disparities, data interoperability, and policy support must be addressed to fully realize the potential of dynamic routing in urban environments. The study concludes by emphasizing the importance of policy interventions and collaborative efforts to overcome these barriers and proposes future research directions to improve scalability and data integration in dynamic routing systems.

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32

Bocewicz, Grzegorz, Grzegorz Radzki, Peter Nielsen, and Zbigniew Banaszak. "UAVs’ Dynamic Routing, Subject to Time Windows Variation." IFAC-PapersOnLine 55, no. 2 (2022): 457–62. http://dx.doi.org/10.1016/j.ifacol.2022.04.236.

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33

Zhu, Yan-Bo, Xiang-Min Guan, and Xue-Jun Zhang. "Heterogeneous delivering capability promotes traffic efficiency in complex networks." International Journal of Modern Physics C 26, no. 06 (2015): 1550069. http://dx.doi.org/10.1142/s0129183115500692.

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Traffic is one of the most fundamental dynamical processes in networked systems. With the homogeneous delivery capability of nodes, the global dynamic routing strategy proposed by Ling et al. [Phys. Rev. E81, 016113 (2010)] adequately uses the dynamic information during the process and thus it can reach a quite high network capacity. In this paper, based on the global dynamic routing strategy, we proposed a heterogeneous delivery allocation strategy of nodes on scale-free networks with consideration of nodes degree. It is found that the network capacity as well as some other indexes reflecting transportation efficiency are further improved. Our work may be useful for the design of more efficient routing strategies in communication or transportation systems.

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34

Selim, Ibrahim Mohsen, Naglaa Sayed Abdelrehem, Walaa M. Alayed, Hesham M. Elbadawy, and Rowayda A. Sadek. "MANET Routing Protocols’ Performance Assessment Under Dynamic Network Conditions." Applied Sciences 15, no. 6 (2025): 2891. https://doi.org/10.3390/app15062891.

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Mobile Ad Hoc Networks (MANETs) are decentralized wireless networks characterized by dynamic topologies and the absence of fixed infrastructure. These unique features make MANETs critical for applications such as disaster recovery, military operations, and IoT systems. However, they also pose significant challenges for efficient and effective routing. This study evaluates the performance of eight MANET routing protocols: Optimized Link State Routing (OLSR), Destination-Sequenced Distance Vector (DSDV), Ad Hoc On-Demand Distance Vector (AODV), Dynamic Source Routing (DSR), Ad Hoc On-Demand Multipath Distance Vector (AOMDV), Temporally Ordered Routing Algorithm (TORA), Zone Routing Protocol (ZRP), and Geographic Routing Protocol (GRP). Using a custom simulation environment in OMNeT++ 6.0.1 with INET-4.5.0, the protocols were tested under four scenarios with varying node densities (20, 80, 200, and 500 nodes). The simulations utilized the Random Waypoint Mobility model to mimic dynamic node movement and evaluated key performance metrics, including network load, throughput, delay, energy consumption, jitter, packet loss rate, and packet delivery ratio. The results reveal that proactive protocols like OLSR are ideal for stable, low-density environments, while reactive protocols such as AOMDV and TORA excel in dynamic, high-mobility scenarios. Hybrid protocols, particularly GRP, demonstrate a balanced approach; achieving superior overall performance with up to 30% lower energy consumption and higher packet delivery ratios compared to reactive protocols. These findings provide practical insights into the optimal selection and deployment of MANET routing protocols for diverse applications, emphasizing the potential of hybrid protocols for modern networks like IoT and emergency response systems.

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35

Zou, Peijun, Ming Zhao, Jia Wu, and Leilei Wang. "Routing Algorithm Based on Trajectory Prediction in Opportunistic Networks." Information 10, no. 2 (2019): 49. http://dx.doi.org/10.3390/info10020049.

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Due to the dynamic change of the opportunistic network topology and the lack of stable information transmission paths between nodes, the traditional topology-based routing algorithm cannot achieve the desired routing performance. To address of this problem, this paper proposes a routing algorithm based on trajectory prediction (RATP). The routing protocol based on trajectory prediction can efficiently and quickly adapt to the network link quality instability and the dynamic changes of network topology. RATP algorithm constructs a node mobility model by analyzing the historical mobility characteristics of the nodes. According to the node prediction information, the metric value of the candidate node is calculated, and the node with the smaller metric value is selected as the data forwarding node, which can effectively reduce the packet loss rate and avoids excessive consumption. Simulation results show that compared with other algorithms, the proposed algorithm has higher data delivery ratio, and end-to-end data delay and routing overhead are significantly reduced.

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36

Cesarone, John, and Kornel F. Eman. "Mobile robot routing with dynamic programming." Journal of Manufacturing Systems 8, no. 4 (1989): 257–66. http://dx.doi.org/10.1016/0278-6125(89)90003-4.

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37

Casas, Pedro, Lionel Fillatre, Sandrine Vaton, and Igor Nikiforov. "Reactive Robust Routing: Anomaly Localization and Routing Reconfiguration for Dynamic Networks." Journal of Network and Systems Management 19, no. 1 (2010): 58–83. http://dx.doi.org/10.1007/s10922-010-9182-9.

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38

Sverdlova, Anastasia D., Artur O. Zaporozhets, Ihor V. Bohachev, et al. "Dynamic routing protocols for wireless touch networks: a review." Journal of Edge Computing 1, no. 1 (2022): 29–42. http://dx.doi.org/10.55056/jec.571.

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Wireless Touch Networks (WTN) have become increasingly important with the emergence of the Internet of Things (IoT) and are regarded as a class of self-organizing networks. This article presents an overview of the construction principles, routing protocols, quality of service parameters, traffic models, and characteristics of WTN. The article also explores the application of dynamic routing protocols for constructing a self-organizing network of autonomous IoT systems. Known dynamic routing protocols for mobile radio networks are reviewed and the advantages and disadvantages of proactive and reactive approaches are discussed.

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39

Ross, Keith W. "Optimal dynamic routing in Markov queueing networks." Automatica 22, no. 3 (1986): 367–70. http://dx.doi.org/10.1016/0005-1098(86)90035-x.

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40

Cheng, Hui. "Dynamic Genetic Algorithms with Hyper-Mutation Schemes for Dynamic Shortest Path Routing Problem in Mobile Ad Hoc Networks." International Journal of Adaptive, Resilient and Autonomic Systems 3, no. 1 (2012): 87–98. http://dx.doi.org/10.4018/jaras.2012010105.

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In recent years, the static shortest path (SP) routing problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks (ANNs), genetic algorithms (GAs), particle swarm optimization (PSO), etc. However, with the advancement in wireless communications, more and more mobile wireless networks appear, e.g., mobile ad hoc network (MANET), wireless mesh network (WMN), etc. One of the most important characteristics in mobile wireless networks is the topology dynamics, that is, the network topology changes over time due to energy conservation or node mobility. Therefore, the SP routing problem in MANETs turns out to be a dynamic optimization problem. This paper proposes to use two types of hyper-mutation GAs to solve the dynamic SP routing problem in MANETs. The authors consider MANETs as target systems because they represent new generation wireless networks. The experimental results show that the two hyper-mutation GAs can quickly adapt to the environmental changes (i.e., the network topology change) and produce good solutions after each change.

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41

Rowell, J. Martin. "Applying Map Databases to Advanced Navigation and Driver Assistance Systems." Journal of Navigation 54, no. 3 (2001): 355–63. http://dx.doi.org/10.1017/s0373463301001503.

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Navigation map databases have evolved during the last 10 years in coverage, content and accuracy to such a degree that they are being used (and considered) for applications beyond vehicle navigation. For a number of advanced driver assistance systems (ADAS) in Europe and North America, the navigation maps are being enhanced to offer new functions. This will complement dynamic route guidance, with location referencing, descriptions of delays, floating car data and re-routeing, all requiring developments in traffic management, road capacity balancing and routing algorithms.

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42

Bhulai, Sandjai. "DYNAMIC ROUTING POLICIES FOR MULTISKILL CALL CENTERS." Probability in the Engineering and Informational Sciences 23, no. 1 (2008): 101–19. http://dx.doi.org/10.1017/s0269964809000096.

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We consider the problem of routing calls dynamically in a multiskill call center. Calls from different skill classes are offered to the call center according to a Poisson process. The agents in the center are grouped according to their heterogeneous skill sets that determine the classes of calls they can serve. Each agent group serves calls with independent exponentially distributed service times. We consider two scenarios. The first scenario deals with a call center with no buffers in the system, so that every arriving call either has to be routed immediately or has to be blocked and is lost. The objective in the system is to minimize the average number of blocked calls. The second scenario deals with call centers consisting of only agents that have one skill and fully cross-trained agents, where calls are pooled in common queues. The objective in this system is to minimize the average number of calls in the system. We obtain nearly optimal dynamic routing policies that are scalable with the problem instance and can be computed online. The algorithm is based on one-step policy improvement using the relative value functions of simpler queuing systems. Numerical experiments demonstrate the good performance of the routing policies. Finally, we discuss how the algorithm can be used to handle more general cases with the techniques described in this article.

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43

Lau, H. Y. K., and S. O. Woo. "An agent-based dynamic routing strategy for automated material handling systems." International Journal of Computer Integrated Manufacturing 21, no. 3 (2008): 269–88. http://dx.doi.org/10.1080/09511920701241624.

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44

Heusse, Martin, Dominique Snyers, Sylvain Guérin, and Pascale Kuntz. "Adaptive Agent-Driven Routing and Load Balancing in Communication Networks." Advances in Complex Systems 01, no. 02n03 (1998): 237–54. http://dx.doi.org/10.1142/s0219525998000168.

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This paper presents an unified overview of a new family of distributed algortithms for routing and load balancing in dynamic communication networks. These new algorithms are described as an extension to the classical routing algorithms: they combine the ideas of online asynchronous distance vector routing with adaptive link state routing. Estimates of the current traffic condition and link costs are measured by sending routing agents in the network that mix with the regular information packets and keep track of the costs (e.g. delay) encountered during their journey. The routing tables are then regularly updated based on that information without any central control nor complete knowledge of the network topology. Two new algorithms are proposed here. The first one is based on round trip routing agents that update the routing tables by backtracking their way after having reached the destination. The second one relies on forward agents that update the routing tables directly as they move toward their destination. An efficient co-operative scheme is proposed to deal with asymmetric connections. All these methods are compared on a simulated network with various traffic loads; the robustness of the new algorithms to network changes is proved on various dynamic scenarii.

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45

Caleffi, Marcello, and Luigi Paura. "M-DART: multi-path dynamic address routing." Wireless Communications and Mobile Computing 11, no. 3 (2011): 392–409. http://dx.doi.org/10.1002/wcm.986.

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46

Xue, Qiubei, Yang Yang, Jie Yang, et al. "QEHLR: A Q-Learning Empowered Highly Dynamic and Latency-Aware Routing Algorithm for Flying Ad-Hoc Networks." Drones 7, no. 7 (2023): 459. http://dx.doi.org/10.3390/drones7070459.

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With the growing utilization of intelligent unmanned aerial vehicle (UAV) clusters in both military and civilian domains, the routing protocol of flying ad-hoc networks (FANETs) has promised a crucial role in facilitating cluster communication. However, the highly dynamic nature of the network topology, owing to the rapid movement and changing direction of aircraft nodes, as well as frequent accesses and exits from the network, has resulted in an increased interruption rate of FANETs links. While traditional protocols can satisfy basic network service quality (QoS) requirements in mobile ad-hoc networks (MANETs) with relatively fixed topology changes, they may fail to achieve optimal routes and consequently restrict information dissemination in FANETs with topology changes, which ultimately leads to elevated packet loss and delay. This paper undertakes an in-depth investigation of the challenges faced by current routing protocols in high dynamic topology scenarios, such as delay and packet loss. It proposes a Q-learning empowered highly dynamic, and latency-aware routing algorithm for flying ad-hoc networks (QEHLR). Traditional routing algorithms are unable to effectively route packets in highly dynamic FANETs; hence, this paper employs a Q-learning method to learn the link status in the network and effectively select routes through Q-values to avoid connection loss. Additionally, the remaining time of the link or path lifespan is incorporated into the routing protocol to construct the routing table. QEHLR can delete predicted failed links based on network status, thereby reducing packet loss caused by failed route selection. Simulations show that the enhanced algorithm significantly improves the packet transmission rate, which addresses the challenge of routing protocols’ inability to adapt to various mobility scenarios in FANETs with dynamic topology by introducing a calculation factor based on the QEHLR protocol. The experimental results indicate that the improved routing algorithm achieves superior network performance.

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Akinola, Oluwaseun Ibrahim. "Adaptive Location-based Routing Protocols for Dynamic Wireless Sensor Networks in Urban Cyber-physical Systems." Journal of Engineering Research and Reports 26, no. 7 (2024): 424–43. http://dx.doi.org/10.9734/jerr/2024/v26i71220.

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This study investigates the development and enhancement of adaptive location-based routing protocols within dynamic wireless sensor networks (WSNs) in urban cyber-physical systems, recommending the implementation of the study’s innovative Urban Adaptive Location-based Routing Protocol (UALRP). This innovative protocol integrates real-time data analytics and adaptive machine learning models into its algorithmic framework to dynamically optimize routing decisions based on continuously changing urban conditions. Through the utilization of data-driven simulation models and machine learning techniques, the research sought to significantly improve the efficiency, reliability, and scalability of urban WSNs. Existing protocols such as Geographic Adaptive Fidelity (GAF), Greedy Perimeter Stateless Routing (GPSR), and Dynamic Source Routing (DSR) were critically assessed under urban settings using extensive datasets detailing New York City's traffic patterns and environmental variables. The analysis demonstrated that while GPSR showed superior performance in terms of latency, throughput, and energy efficiency among the traditional protocols, the introduction of UALRP, with its advanced predictive and adaptive capabilities, can further optimize these metrics. The study affirms the critical role of enhancing location accuracy and the ongoing advancement of machine learning models within urban routing protocols. These insights advocate for the broader implementation of adaptive strategies like UALRP to foster the development of more resilient and efficient urban cyber-physical systems.

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Dzyubak, S. A., V. A. Berdutin, and T. E. Romanova. "Intelligent computer system for dynamic routing of outpatient patients." Glavvrač (Chief Medical Officer), no. 9 (September 27, 2024): 6–17. http://dx.doi.org/10.33920/med-03-2409-01.

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Insufficient logistical efficiency in organizing the flow of patients when visiting an outpatient clinic is an urgent public health problem that negatively affects the qualitative and quantitative characteristics of medical care. Reducing waiting time for an appointment at a doctor’s office and optimal routing of various categories of patients creates a reliable basis for providing high-quality and affordable medical care in healthcare institutions. In the modern world, these goals can be achieved using innovative intelligent computer routing systems. The article presents the experience of implementing such a system in a polyclinic.

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Macharet, Douglas G., and Mario F. M. Campos. "A survey on routing problems and robotic systems." Robotica 36, no. 12 (2018): 1781–803. http://dx.doi.org/10.1017/s0263574718000735.

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SUMMARYPlanning paths that are length or time optimized or both is an age-long problem for which numerous approaches have been proposed with varied degree of success depending on the imposed constraints. Among classical instances in the literature, the Traveling Salesman Problem and the Vehicle Routing Problem have been widely studied and frequently considered in the realm of mobile robotics. Understandably, the classical formulation for such problems do not take into account many different issues that arise in real-world scenarios, such as motion constraints and dynamic environments, commonly found in actual robotic systems, and consequently the solutions have been generalized in several ways. In this work, we present a broad and comprehensive review of the classical works and recent breakthroughs regarding the routing techniques ordinarily used in robotic systems and provide references to the most fundamental works in the literature.

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S, Sathish, and Deepa S. "Analysis of Route Discovery in Mobile ad-hoc Network Routing using Information Systems." International Journal of Computer Science and Engineering Communications 1, no. 1 (2013): 6–12. https://doi.org/10.5281/zenodo.821734.

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Mobile Ad hoc NET works (MANETs) are group of wireless mobile nodes that can dynamically form a network without any infrastructures wherein mobile nodes are highly co-operative. In MANETs, the movement of nodes is uncertain may cause links to break and low battery life of mobile nodes may cause nodes to fail. The connectivity of the entire network is uncertain and may not be known to any particular node. The work presented in this studies routing in cache-based ad hoc routing protocols, based on the Information Systems of Rough Set Theory (RST). The Rough Set Theory is a new mathematical tool to deals with vagueness and uncertainty and applied for cache based routing protocols in MANETs. The cache in mobile nodes looks similar to the information system of Rough Set Theory. The direct use of information systems in mobile nodes are used to assist routing of data packets and the decision systems are used to predict the next hop for a destination in MANETs.

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