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Intent-Driven Campus Network Deployment Practices
Published in Ningguo Shen, Bin Yu, Mingxiang Huang, Hailin Xu, Campus Network Architectures and Technologies, 2021
Ningguo Shen, Bin Yu, Mingxiang Huang, Hailin Xu
Network design is a process of designing a proper network architecture and technical solution based on the network environment and service requirements of customers. Different scenarios have varying network requirements for reliability, security, and usability, so a good understanding of network requirements and network status is the foundation for a successful network design. The network design process starts with a survey of the customer’s requirements, followed by a thorough analysis, based on which a network solution can be carefully designed. Figure 10.1 shows the network design process.
Utilizing Artificial Intelligence to Design Delay and Energy-Aware Wireless Sensor Networks
Published in Puneet Kumar, Vinod Kumar Jain, Dharminder Kumar, Artificial Intelligence and Global Society, 2021
Ranjana Thalore, Vandita Vyas, Jeetu Sharma, Vikas Raina
Information from the physical world is obtained by WSNs through sensing the physical properties of various objects. The need for network systems varies according to different applications. This leads to variation in different hardware and software platforms and communication protocols. To attain reliable and efficient system objectives, the network design should be related to the specific application.
Resilient supply chain to a global pandemic
Published in International Journal of Production Research, 2023
Mohamed R. Salama, Ronald G. McGarvey
In this section, we investigate the influence of four key factors on the SC network design, namely the initial cost to include a node in the SC design, the network topology, number of worst scenarios (θ) to be considered in the design process and the minimum allowable production percentage required for a node to be included in the SC design. Table 5 shows, in the first three columns, the four factors, their tested levels, and whether a pandemic disruption is active, while the remaining columns exhibit the resultant SC design identified by the optimisation model for each factor level in terms of the number of selected nodes and which nodes are included with respect to the SC network in Figure 3. For all the experiments in this section, the objective is maximizing the overall expected profit (i.e. ) unless otherwise stated.
Multiline holding based control for lines merging to a shared transit corridor
Published in Transportmetrica B: Transport Dynamics, 2019
Georgios Laskaris, Oded Cats, Erik Jenelius, Marco Rinaldi, Francesco Viti
The majority of an urban network’s demand is usually concentrated onto areas along key corridors. As a result, multiple public transport lines often share a set of consecutive stops along their route to cater for the high-demand section. This solution yields denser services with shorter headways, hence reducing the need to perform transfers and in turn increasing public transport’s attractiveness. Network design subject to passenger cost minimization has been shown to result in such a network topology (Baaj and Mahmassani 1995). From the operations perspective, networks with a shared transit corridor have mostly been addressed at the tactical planning level by designing timetables for buses that share stops to minimize waiting times (Guihaire and Hao 2010) and maximize the number of synchronization events (Ceder, Golany, and Tal 2001). In the case of a joint schedule, buses follow a specific sequence of arrivals at the common parts to reduce the congestion of the transit corridor and to provide shorter waiting times for the passengers at these stops (Ibarra-Rojas and Muñoz 2015).
A review of fleet planning problems in single and multimodal transportation systems
Published in Transportmetrica A: Transport Science, 2019
Adil Baykasoğlu, Kemal Subulan, A. Serdar Taşan, Nurhan Dudaklı
An intermodal logistics network design model with a hybrid network topology was developed by Ezabadi and Vergara (2016) to solve integrated terminal/hub location, transportation mode and route selection problems. They employed a two-stage optimization approach by decomposing the original problem into master and multiple sub-problems. Mixed-integer non-linear and non-convex programs were developed by Wang and Meng (2017) a discrete intermodal network design problem for freight transportation. The congestion effects, route choice behavior of intermodal operators and piecewise linear cost functions were also covered. Fotuhi and Huynh (2018) presented a mixed-integer probabilistic robust mathematical model to handle the uncertainties of demand and supply in an intermodal freight network expansion problem. They indeed targeted to decide on the locations of new intermodal terminals and amount of capacity addition to the existing terminals. Although the aforementioned multi-modal load or freight planning and network design problems are not directly associated with intermodal fleet management, they constitute important inputs of the intermodal fleet planning.