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Structural Controllability in Managing Disruptions in Supply Networks
Published in Shabnam Rezapour, Amirhossein Khosrojerdi, Golnoosh Rasoulifar, Janet K. Allen, Jitesh H. Panchal, Ramakrishnan S. Srinivasan, Jeffrey D. Tew, Farrokh Mistree, Architecting Fail-Safe Supply Networks, 2018
Shabnam Rezapour, Amirhossein Khosrojerdi, Golnoosh Rasoulifar, Janet K. Allen, Jitesh H. Panchal, Ramakrishnan S. Srinivasan, Jeffrey D. Tew, Farrokh Mistree
Graphs are mathematical structures that are used to model the pairing oriented relations between objects of a certain collection. The study of graphs began in the 18th century and graph theory is now an important area of study within the discipline of discrete mathematics. Furthermore, graph theory has emerged as a particularly useful method for solving practical problems. Network theory is a segment of study within graph theory that scrutinizes the networks of real systems. Networks permeate a multitude of disciplines. Thus its applications range from the internet to biological systems. This discipline also introduces the foundational definitions and theorems of structural controllability. Thulasiraman and Swamy (1992) elucidate the concepts and fundamental definitions of graph theory itself.
Key nodes mining for complex networks based on local gravity model
Published in Journal of Control and Decision, 2023
Tao Ren, Shixiang Sun, Yanjie Xu, Georgi Marko Dimirovski
The rapid development of information technology, driven by its various and very many applications to everyday economy and life activities, accelerates again the vigorous development of network science in recent decades. Network theory is an important tool to characterise and analyse the structure and function of complex systems in real world from transportation networks and power grids via business to social networks as well as biological networks, etc. (Basaras et al., 2017; Lü et al., 2016a). Generally, in large complex networks (Dimirovski, 2016, 2017), all the nodes do not possess the same importance regarding information propagation and/or disease spreading, among other features characterising investigated networks. Therefore, it is a rather important task problem to identify the nodes within networks that are most likely to be influential in some sense: (1) to restrain the spread of diseases or rumours (Pastor & Vespignani, 2002), hence some influential users need to be quarantined; (2) to maximise the influence range of viral marketing (Richardson & Domingos, 2002), hence most influential nodes are selected as seed nodes to start the marketing process; (3) cascade failures of power grids ought to be prevented to avoid disasters(Albert et al., 2004; Salavati et al., 2018), hence some crucial grid nodes need special protection; and so on for other reasons. This study attempt to enter into the core difficulties of such algorithms.
Evaluation of the structural complexity of organisations and products in naval-shipbuilding projects
Published in Ships and Offshore Structures, 2021
Luis Carral, Javier Tarrío-Saavedra, Gregorio Iglesias, José R. San-Cristobal
Descriptive metrics and visualisation techniques corresponding to statistical net analysis are applied to describe the organisation net of each project and to measure its complexity degree. Network analysis is the area devoted to analyse networks using the network theory, also known by the generic name of graph theory (Scott and Carrington 2011; Luke 2015). Network analysis has been increasingly developed due to the need of studying and extracting information from social, internet, information, transport, electrical, biological networks, among others (Scott and Carrington 2011; Luke 2015). Visualisation techniques, measures of centralisation and complexity, critical routes studies (in Program Evaluation and Review Technique, PERT), net dynamics studies, pattern recognition and identification of groups are task commonly used in this field (Scott and Carrington 2011). The R free software is a very useful alternative to implement net analysis (Luke 2015). In fact, the igraph (Csardi and Nepusz 2006), graph (Gentleman et al. 2017) and QuACN (Mueller et al. 2010) packages have been used to perform descriptive analysis and complexity measurements of the shipbuilding projects organisations.
A resilience assessment of an interdependent multi-energy system with microgrids
Published in Sustainable and Resilient Infrastructure, 2021
Network theory is a subset of graph theory which is used to study interacting systems. Some classic examples of network theory applications are the shortest path problem, critical path assessment, or maximum flow analysis. Nodes and edges in a network have attributes that represent the system of interest. For the MES application, the nodes in an MES network may represent supply/demand quantity, generator/consumer location, or different subsystems (generators, transformers, compressors) in an energy sector. Edges in an MES network may represent, in most cases, the capacity of energy flow (unidirectional) or energy exchange situation (bidirectional).