Modeling and assessing interdependencies between critical infrastructures using Bayesian network: A case study of inland waterway port and surrounding supply chain network

[1]  Mohammad Marufuzzaman,et al.  A Bayesian network based approach for modeling and assessing resilience: A case study of a full service deep water port , 2019, Reliab. Eng. Syst. Saf..

[2]  Mohammad Marufuzzaman,et al.  A framework for modeling and assessing system resilience using a Bayesian network: A case study of an interdependent electrical infrastructure system , 2019, Int. J. Crit. Infrastructure Prot..

[3]  Charles B. Keating,et al.  A systemic approach for disruption risk assessment in oil and gas supply chains , 2019, Int. J. Crit. Infrastructures.

[4]  Jing Lin,et al.  Application of Bayesian Networks in Reliability Evaluation , 2019, IEEE Transactions on Industrial Informatics.

[5]  Lei Jiang,et al.  Bayesian Networks for Reliability Engineering , 2019 .

[6]  Seyedmohsen Hosseini,et al.  Development of a Bayesian network model for optimal site selection of electric vehicle charging station , 2019, International Journal of Electrical Power & Energy Systems.

[7]  Zachary A. Collier,et al.  Stakeholder mapping and disruption scenarios with application to resilience of a container port , 2019, Reliab. Eng. Syst. Saf..

[8]  Di Zhang,et al.  Resilience in transportation systems: a systematic review and future directions , 2018 .

[9]  Lu Zhen,et al.  Tug scheduling for hinterland barge transport: A branch-and-price approach , 2018, Eur. J. Oper. Res..

[10]  Iris Tien,et al.  Probabilistic multi-scale modeling of interdependencies between critical infrastructure systems for resilience , 2018 .

[11]  A. Gharehgozli,et al.  Evaluating a “wicked problem”: A conceptual framework on seaport resiliency in the event of weather disruptions , 2017 .

[12]  D. Shaw,et al.  Multi-level port resilience planning in the UK: how can information sharing be made easier? , 2017 .

[13]  Mohammad Marufuzzaman,et al.  Sustainable network design for multi-purpose pellet processing depots under biomass supply uncertainty , 2017, Comput. Ind. Eng..

[14]  James P. Bagrow,et al.  Reducing Cascading Failure Risk by Increasing Infrastructure Network Interdependence , 2017, Scientific Reports.

[15]  H. Nachtmann,et al.  Economic impact analysis of inland waterway disruption response , 2017 .

[16]  Norman E. Fenton,et al.  A Bayesian network framework for project cost, benefit and risk analysis with an agricultural development case study , 2016, Expert Syst. Appl..

[17]  Kash Barker,et al.  A Bayesian network model for resilience-based supplier selection , 2016 .

[18]  Christophe Champod,et al.  Using sensitivity analyses in Bayesian Networks to highlight the impact of data paucity and direct future analyses: a contribution to the debate on measuring and reporting the precision of likelihood ratios. , 2016, Science & justice : journal of the Forensic Science Society.

[19]  Jasmine Siu Lee Lam,et al.  A quality function deployment approach to improve maritime supply chain resilience , 2016 .

[20]  Anming Zhang,et al.  Internalization of port congestion: strategic effect behind shipping line delays and implications for terminal charges and investment , 2016 .

[21]  Kash Barker,et al.  Modeling infrastructure resilience using Bayesian networks: A case study of inland waterway ports , 2016, Comput. Ind. Eng..

[22]  Thomas L. Landers,et al.  Dynamic impacts of commodity flow disruptions in inland waterway networks , 2015, Comput. Ind. Eng..

[23]  Jan Fransoo,et al.  A decision support system tool for the transportation by barge of import containers: A case study , 2015, Decis. Support Syst..

[24]  Leire Labaka,et al.  Resilience framework for critical infrastructures: An empirical study in a nuclear plant , 2015, Reliab. Eng. Syst. Saf..

[25]  María M. Abad-Grau,et al.  Points of Significance: Bayesian networks , 2015, Nature Methods.

[26]  Min Ouyang,et al.  Resilience assessment of interdependent infrastructure systems: With a focus on joint restoration modeling and analysis , 2015, Reliab. Eng. Syst. Saf..

[27]  Prasanta Kumar Dey,et al.  Strategic sourcing supplier selection misalignment with critical success factors:findings from multiple case studies in Germany and the United Kingdom , 2015 .

[28]  Stavros Ntalampiras,et al.  Analysis of Critical Infrastructure Network Failure in the European Union: A Combined Systems Engineering and Economic Model , 2015 .

[29]  William Ho,et al.  Supply chain risk management: a literature review , 2015 .

[30]  V. Gekara,et al.  Seaport resilience to climate change: mapping vulnerability to sea-level rise , 2015 .

[31]  A. Becker,et al.  Stakeholder Perceptions of Seaport Resilience Strategies: A Case Study of Gulfport (Mississippi) and Providence (Rhode Island) , 2015 .

[32]  Abdollah Shafieezadeh,et al.  Scenario-based resilience assessment framework for critical infrastructure systems: Case study for seismic resilience of seaports , 2014, Reliab. Eng. Syst. Saf..

[33]  Maria Hänninen,et al.  Bayesian network model of maritime safety management , 2014, Expert Syst. Appl..

[34]  M. Korkali,et al.  Reducing Cascading Failure Risk by Increasing Infrastructure Network Interdependency , 2014, ArXiv.

[35]  Cheng-Hsien Hsieh,et al.  Port vulnerability assessment from the perspective of critical infrastructure interdependency , 2014 .

[36]  Hui Shan Loh,et al.  Managing port-related supply chain disruptions: A conceptual paper , 2014 .

[37]  Andrew Grainger,et al.  Port resilience: a primer , 2014 .

[38]  Kash Barker,et al.  Importance measures for inland waterway network resilience , 2014 .

[39]  Chase Rainwater,et al.  Optimal Dredge Fleet Scheduling within Environmental Work Windows , 2014 .

[40]  Inge Norstad,et al.  Optimization, risk assessment and resilience in LNG transportation systems , 2013 .

[41]  Kash Barker,et al.  Resilience-based network component importance measures , 2013, Reliab. Eng. Syst. Saf..

[42]  Yongtae Park,et al.  Assessing the risks of service failures based on ripple effects: A Bayesian network approach , 2013 .

[43]  Daniel DeLaurentis,et al.  Evaluating System of Systems resilience using interdependency analysis , 2012, 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[44]  Mayada Omer,et al.  A framework for assessing resiliency of maritime transportation systems , 2012 .

[45]  Norman Fenton,et al.  Risk Assessment and Decision Analysis with Bayesian Networks , 2012 .

[46]  Jasmine Siu Lee Lam,et al.  Impact of Port Disruption on Supply Chains: A Petri Net Approach , 2012, ICCL.

[47]  Joost R. Santos,et al.  Measuring changes in international production from a disruption: Case study of the Japanese earthquake and tsunami , 2012 .

[48]  Paul Krause,et al.  Bayesian Networks for the management of greenhouse gas emissions in the British agricultural sector , 2012, Environ. Model. Softw..

[49]  Alfredo Vellido,et al.  Classification of human brain tumours from MRS data using Discrete Wavelet Transform and Bayesian Neural Networks , 2012, Expert Syst. Appl..

[50]  Kash Barker,et al.  Evaluating the Consequences of an Inland Waterway Port Closure With a Dynamic Multiregional Interdependence Model , 2012, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[51]  Bjørn Egil Asbjørnslett,et al.  Failure modes in the maritime transportation system: a functional approach to throughput vulnerability , 2011 .

[52]  Pengcheng Zhang,et al.  A generalized modeling framework to analyze interdependencies among infrastructure systems , 2011 .

[53]  Iraj Mahdavi,et al.  A multi-objective decision-making process of supplier selection and order allocation for multi-period scheduling in an electronic market , 2011 .

[54]  R. Gurning,et al.  SUPPLY CHAIN RISK MANAGEMENT STRATEGIES FOR MANAGING MARITIME DISRUPTIONS DUE TO THE EFFECTS OF CLIMATE CHANGE EVIDENCE FROM THE AUSTRALIAN INDONESIAN WHEAT SUPPLY CHAIN , 2010 .

[55]  Elise Miller-Hooks,et al.  Resilience Framework for Ports and Other Intermodal Components , 2010 .

[56]  Johan Woxenius,et al.  The dry port concept: connecting container seaports with the hinterland , 2009 .

[57]  Stephen Cahoon,et al.  Analysis of random disruptive events in shipping and port operations , 2009 .

[58]  Benoît Rozel.  La sécurisation des infrastructures critiques : recherche d'une méthodologie d'identification des vulnérabilités et modélisation des interdépendances , 2009 .

[59]  Photis M. Panayides,et al.  A Critical Analysis of DEA Applications to Seaport Economic Efficiency Measurement , 2009 .

[60]  Brian Slack,et al.  Inland barge services and container transport: the case of the ports of Le Havre and Marseille in the European context , 2009 .

[61]  Joost R. Santos,et al.  International Trade Inoperability Input‐Output Model (IT‐IIM): Theory and Application , 2009, Risk analysis : an official publication of the Society for Risk Analysis.

[62]  Sergio Jara-Díaz,et al.  Productivity in Cargo Handling in Spanish Ports During a Period of Regulatory Reforms , 2008 .

[63]  Lalit Mohan Saini,et al.  Peak load forecasting using Bayesian regularization, Resilient and adaptive backpropagation learning based artificial neural networks , 2008 .

[64]  D. Winterfeldt,et al.  A Risk and Economic Analysis of Dirty Bomb Attacks on the Ports of Los Angeles and Long Beach , 2007, Risk analysis : an official publication of the Society for Risk Analysis.

[65]  Steven M. Rinaldi,et al.  Modeling and simulating critical infrastructures and their interdependencies , 2004, 37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the.

[66]  Teresa M Adams,et al.  Optimization of mechanical dredging operations for sediment remediation , 2001 .

[67]  Rae Zimmerman,et al.  Social Implications of Infrastructure Network Interactions , 2001 .

[68]  Pablo Coto-Millán,et al.  Economic efficiency in Spanish ports: some empirical evidence , 2000 .

[69]  D. Geiger,et al.  Learning Bayesian networks: The combination of knowledge and statistical data , 1994, Machine Learning.

[70]  Max Henrion,et al.  Practical issues in constructing a Bayes belief network , 1987, Int. J. Approx. Reason..

[71]  Beatriz Tovar,et al.  Heterogeneity unobserved and efficiency: a latent class model for west coast of South Pacific port terminals , 2017 .

[72]  Jin Wang,et al.  A risk assessment approach to improve the resilience of a seaport system using Bayesian networks , 2016 .

[73]  Logan Perreault,et al.  A Noisy-OR Model for Continuous Time Bayesian Networks , 2016, FLAIRS.

[74]  Alan Wall,et al.  Can ports increase traffic while reducing inputs? Technical efficiency of Spanish Port Authorities using a directional distance function approach , 2015 .

[75]  Beatriz Tovar,et al.  Efficiency and productivity changes for Peruvian and Chilean ports terminals: A parametric distance functions approach , 2014 .

[76]  Fazleena Badurdeen,et al.  A Bayesian Network Based Approach for Risk Modeling to Aid in Development of Sustainable Biomass Supply Chains , 2012 .

[77]  P. Hokstad,et al.  Risk and Interdependencies in Critical Infrastructures , 2012 .

[78]  Rudolph Frederick Stapelberg,et al.  Infrastructure Systems Interdependencies and Risk Informed Decision Making (RIDM): Impact Scenario Analysis of Infrastructure Risks Induced by Natural, Technological and Intentional Hazards , 2008 .

[79]  R. James Barbour,et al.  Strategic assessment of bioenergy development in the West : spatial analysis and supply curve development : final report, The University of California, Davis, September 1, 2008 , 2008 .

[80]  Stephanie E. Chang,et al.  Disasters and transport systems: loss, recovery and competition at the Port of Kobe after the 1995 earthquake , 2000 .

[81]  The Aquila Digital Community The Aquila Digital Community Metrics for Assessing Overall Performance of Inland Waterway Metrics for Assessing Overall Performance of Inland Waterway Ports: A Bayesian Network Based Approach Ports: A Bayesian Network Based Approach , 2022 .

[82]  P. Gordon,et al.  Journal of Homeland Security and Emergency Management the Economic Impacts of Dirty Bomb Attacks on the Los Angeles and Long Beach Ports: Applying the Supply-driven Niemo (national Interstate Economic Model) Foreign Import Ports Volumn ($m) , 2022 .