Journal of Systems Engineering and Electronics ›› 2018, Vol. 29 ›› Issue (5): 995-1008.doi: 10.21629/JSEE.2018.05.11

• Systems Engineering • Previous Articles     Next Articles

Towards optimal recovery scheduling for dynamic resilience of networked infrastructure

Yang WANG1(), Shanshan FU2(), Bing WU1(), Jinhui HUANG1(), Xiaoyang WEI3,*()   

  1. 1 Intelligent Transportation System Research Center, Wuhan University of Technology, Wuhan 430063, China
    2 College of Ocean Science and Engineering, Shanghai Maritime University, Shanghai, 201306, China
    3 Department of Civil and Environmental Engineering, National University of Singapore, Singapore 118414, Singapore
  • Received:2017-08-01 Online:2018-10-26 Published:2018-11-14
  • Contact: Xiaoyang WEI E-mail:wangyang.itsc@whut.edu.cn;fushanshan_lemon@163.com;bing.wu@whut.edu.cn;huangjinhui@whut.edu.cn;weixiaoyang@u.nus.edu
  • About author:WANG Yang was born in 1976. He received his B.S. degree in mathematics from Wuhan University in 1997, M.S. degree in applied mathematics from Shanghai Jiao Tong University in 2000, and Ph.D. degree in computer science from Huazhong University of Science and Technology in 2008. He is currently an associate professor in Intelligent Transportation Systems Research Center of Wuhan University of Technology. His main research interest is transportation safety, including system resilience, risk assessment and emergency disposition. He is also conducting research on the human factors in the transportation system by developing simulation environment for humanmachine interaction measurement and group performance modeling. E-mail: wangyang.itsc@whut.edu.cn|FU Shanshan was born in 1987. She received her B.E. degree in logistics engineering, M.S. degree in intelligent transportation engineering and Ph.D. degree in vehicle operation engineering from Wuhan University of Technology in 2010, 2013 and 2017 respectively. She was a research assistant at National Engineering Research Center for Water Transport Safety, from 2012 to 2016. She is currently a lecturer in the College of Ocean Science and Engineering, Shanghai Maritime University. Her main research interests include resilience analysis of transportation systems, risk modeling of arctic shipping and uncertainty modeling in quantitative risk assessment. E-mail: fushanshan_lemon@163.com|WU Bing was born in 1986. He received his B.E. degree in navigation technology from School of Navigation, M.E. degree in traffic information engineering and control from School of Navigation, and Ph.D. degree in traffic engineering from School of Energy and Power Engineering, Wuhan University of Technology in 2008, 2012, and 2016 respectively. During the period from 2014 to 2015, he was a joint Ph.D. student in University of Lisbon. He is currently an assistant professor in Intelligent Transportation System Center of Wuhan University of Technology. His main research interests include risk analysis, decision making and human reliability analysis for transportation systems. E-mail: bing.wu@whut.edu.cn|HUANG Jinhui was born in 1992. He received his B.E. degree in energy power system and automation from School of Energy and Power Engineering, Wuhan University of Technology in 2015. He is currently a master student in major of traffic and transportation engineering at Wuhan University of Technology. His main research interests include traffic accident modeling, organization resilience analysis, performance evaluation of emergency disposal and related fields. E-mail: huangjinhui@whut.edu.cn|WEI Xiaoyang was born in 1990. He received his B.E. degree in navigation technology from School of Navigation, M.E. degree in communication and transportation engineering from School of Energy and Power Engineering, Wuhan University of Technology in 2014 and 2017 respectively. He is currently a Ph.D. student in Department of Civil and Environmental Engineering, National University of Singapore. His main research interests include machine learning, risk analysis and accident consequence assessment for transportation systems. E-mail: weixiaoyang@u.nus.edu
  • Supported by:
    the National Natural Science Foundation of China(51479158);the Fundamental Research Funds for the Central Universities(WUT: 2018III061GX);This work was supported by the National Natural Science Foundation of China (51479158) and the Fundamental Research Funds for the Central Universities (WUT: 2018III061GX)

Abstract:

Prior research on the resilience of critical infrastructure usually utilizes the network model to characterize the structure of the components so that a quantitative representation of resilience can be obtained. Particularly, network component importance is addressed to express its significance in shaping the resilience performance of the whole system. Due to the intrinsic complexity of the problem, some idealized assumptions are exerted on the resilience-optimization problem to find partial solutions. This paper seeks to exploit the dynamic aspect of system resilience, i.e., the scheduling problem of link recovery in the post-disruption phase. The aim is to analyze the recovery strategy of the system with more practical assumptions, especially inhomogeneous time cost among links. In view of this, the presented work translates the resilience-maximization recovery plan into the dynamic decisionmaking of runtime recovery option. A heuristic scheme is devised to treat the core problem of link selection in an ongoing style. Through Monte Carlo simulation, the link recovery order rendered by the proposed scheme demonstrates excellent resilience performance as well as accommodation with uncertainty caused by epistemic knowledge.

Key words: dynamic resilience, network model, component importance, recovery scheduling, epistemic uncertainty