Modeling and Resilience Recovery for Disrupted Supply Chain

Erscheinungsjahr 2026
ISBN: 978-981-954900-9
Verlag: Springer

Buch, Englisch, 214 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 516 g

This book focuses on supply chain management, specifically resilience modeling and recovery strategies for disruptions. It combines multi-level analysis (system, product, event, network) with practical tools such as knowledge graphs, optimization techniques, and risk management frameworks. Key features include a structured, visual approach to complex concepts and multiple recovery dimensions (short-term fixes, product redesign, hierarchical optimization, control support). Blending theory with real-world applications, it provides readers with actionable insights to anticipate risk, optimize operations, and effectively implement recovery plans. Ideal for professionals and students, the book bridges academic research and industry needs, empowering teams to build adaptive, disruption-resistant supply chains in uncertain environments.

Zielgruppe

Research

Autoren/Hrsg.

Peng, Chen

Wang, Hongfeng

Yang, Yi

Zhang, Yong

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Optimierung
• Technische Wissenschaften Technik Allgemein Technik: Allgemeines
• Wirtschaftswissenschaften Betriebswirtschaft Management
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Regelungstechnik

Inhaltsverzeichnis

Introduction.- A knowledge graph driven risk management framework.- Product change modeling with multi objective optimization.- Petri net based modeling on operational and structural dynamics.- Decision modeling with risk cascading propagation effects.- A prediction based recovery strategy under demand dynamics.- Recovery strategy incorporated into product changes and lifecycles.- Recovery through decomposition based optimization.- Coevolution recovery assisted by cost guaranteed control under uncertainties.

Über Autor(innen)

Chen Peng received the Ph.D. degree in control theory and control engineering from the Chinese University of Mining Technology, Xuzhou, China, in 2002.

From November 2004 to January 2005, he was a Research Associate with the University of Hong Kong, Hong Kong. From July 2006 to August 2007, he was a Visiting Scholar with the Queensland University of Technology, Brisbane, QLD, Australia. From July 2011 to August 2012, he was a Postdoctoral Research Fellow with Central Queensland University, Rockhampton, QLD, Australia. In 2012, he was appointed as an Eastern Scholar with the Municipal Commission of Education, Shanghai, China, and joined Shanghai University, Shanghai, where he is currently the Director with the Centre of Networked Control Systems and a Distinguished Professor. In 2018, he was appointed as an Outstanding Academic Leader with the Municipal Commission of Science and Technology, Shanghai. His current research interests include networked control systems, supply chain, optimizated control, CPS.

Prof. Peng is an Associate Editor of a number of international journals, including the IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, Information Sciences, and Transactions of the Institute of Measurement and Control and so on. He was named a Highly Cited Researcher from 2020 to 2024 by Clarivate Analytics.

Hongfeng Wang received the B.Sc. degree in industrial engineering and the M.Sc. and Ph.D. degrees in system engineering from Northeastern University, Shenyang, China, in 2001, 2004, and 2007, respectively. He is a professor with the Institute of System Engineering, Northeastern University. He is the author or coauthor of over 70 refereed technical papers and refereed conference papers, and he is a coauthor of two books on optimization algorithms. His major research interests include evolutionary algorithms, mimetic computing, computational intelligence in dynamic environments, and the modeling of the optimization of complex systems.

Yi Yang was born in Jiangsu province, China, in 1995. He is working toward the Ph.D. degree in control science and engineering with the School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China. His current research interests include supply chain risk management, modeling and change control of product, and supply chain system.

Yong Zhang received the B.S. from Liaocheng University in 1999 and the M.S. and Ph.D. degrees from the China University of Mining and Technology in 2003 and 2009. He is a professor at the China University of Petroleum (East China), Xuzhou. His fields of interest are Machine Vision, Intelligent Optimization Methods and Applications, Mining Integrated Energy Systems, and Big Data Analytics.