A grey analytic network process (ANP) model to identify storm tide risk

Storm tide risk is a function of many factors, besides it is dynamic and complex. There may be relations and dependencies among the risk related factors. Therefore, storm tide risk should be analyzed in a holistic manner. In this study, the storm tide risk (STR) which is tried to be determined through analytical network process (ANP) which is an extension of analytical hierarchy process and allows analysis of complex systems. Besides, there are many difficulties and limitations in measuring the faulty behavior factors. For this reason, the weights of factors and sub-factors which are necessary to calculate the FBR are determined by using grey ANP and by this way it is possible to make better decisions in this process.

[1]  M. Bohanec,et al.  The Analytic Hierarchy Process , 2004 .

[2]  Da Ruan,et al.  Fuzzy group decision-making for facility location selection , 2003, Inf. Sci..

[3]  Stephen F. Wornom,et al.  On Coupling the Swan and Wam Wave Models for Accurate Nearshore Wave Predictions , 2001 .

[4]  Cengiz Kahraman,et al.  Operating system selection using fuzzy replacement analysis and analytic hierarchy process , 2005 .

[5]  T. Saaty.  Decision making — the Analytic Hierarchy and Network Processes (AHP/ANP) , 2004 .

[6]  Y. S. Li,et al.  DYNAMIC COUPLING OF WAVE AND SURGE MODELS BY EULERIAN-LAGRANGIAN METHOD , 1997 .

[7]  T. Saaty,et al.  Dependence and independence: From linear hierarchies to nonlinear networks , 1986 .

[8]  Joseph Sarkis,et al.  Analyzing organizational project alternatives for agile manufacturing processes: An analytical network approach , 1999 .

[9]  Gülçin Büyüközkan,et al.  A fuzzy optimization model for QFD planning process using analytic network approach , 2006, Eur. J. Oper. Res..

[10]  P. Janssen.  Quasi-linear Theory of Wind-Wave Generation Applied to Wave Forecasting , 1991 .

[11]  Klaus Seeland,et al.  The 2004 tsunami in Aceh and Southern Thailand: A review on coastal ecosystems, wave hazards and vulnerability , 2008 .

[12]  Thomas L. Saaty,et al.  Decision making with dependence and feedback : the analytic network process : the organization and prioritization of complexity , 1996 .

[13]  Da Ruan,et al.  Fuzzy group decision making for selection among computer integrated manufacturing systems , 2003, Comput. Ind..

[14]  T Furuichi,et al.  A fuzzy analytic network process for multi-criteria evaluation of contaminated site remedial countermeasures. , 2008, Journal of environmental management.

[15]  Ching-Hsue Cheng,et al.  Evaluating attack helicopters by AHP based on linguistic variable weight , 1999, Eur. J. Oper. Res..

[16]  Pedro Osuna,et al.  A coupling module for tides, surges and waves , 2000 .

[17]  Peter A. E. M. Janssen,et al.  The dynamical coupling of a wave model and a storm surge model through the atmospheric boundary layer , 1993 .

[18]  J. Bao,et al.  Numerical Simulations of Air-Sea Interaction under High Wind Conditions Using a Coupled Model: A Study of Hurricane Development , 2000 .

[19]  T. L. Saaty,et al.  Decision making with dependence and feedback , 2001 .

[20]  R. Flather,et al.  Existing operational oceanography , 2000 .

[21]  Thomas L. Saaty,et al.  Diagnosis with Dependent Symptoms: Bayes Theorem and the Analytic Hierarchy Process , 1998, Oper. Res..

[22]  T. Saaty.  Fundamentals of the analytic network process — Dependence and feedback in decision-making with a single network , 2004 .

[23]  Metin Dagdeviren,et al.  Using the analytic network process (ANP) in a SWOT analysis - A case study for a textile firm , 2007, Inf. Sci..

[24]  Kwok Fai Cheung,et al.  Modeling of tropical cyclone winds and waves for emergency management , 2003 .