A multi-criteria decision analysis approach for importance identification and ranking of network components

Analyzing network vulnerability is a key element of network planning in order to be prepared for any disruptive event that might impact the performance of the network. Hence, many importance measures have been proposed to identify the important components in a network with respect to vulnerability and rank them accordingly based on individual importance measure. However, in this paper, we propose a new approach to identify the most important network components based on multiple importance measures using a multi criteria decision making (MCDM) method, namely the technique for order performance by similarity to ideal solution (TOPSIS), able to take into account the preferences of decision-makers. We consider multiple edge-specific flow-based importance measures provided as the multiple criteria of a network where the alternatives are the edges. Accordingly, TOPSIS is used to rank the edges of the network based on their importance considering multiple different importance measures. The proposed approach is illustrated through different networks with different densities along with the effects of weighs.

[1]  D. R. Fulkerson,et al.  Maximal Flow Through a Network , 1956 .

[2]  D. Ahmad,et al.  Concept selection of car bumper beam with developed hybrid bio-composite material , 2011 .

[3]  Jungyul Sohn,et al.  Evaluating the significance of highway network links under the flood damage: An accessibility approach , 2006 .

[4]  P Venkateswara Rao,et al.  Attribute based specification, comparison and selection of feed stock for anaerobic digestion using MADM approach. , 2011, Journal of hazardous materials.

[5]  Claudio M. Rocco Sanseverino,et al.  Innovative approaches for addressing old challenges in component importance measures , 2012, Reliab. Eng. Syst. Saf..

[6]  H. Hassel,et al.  Vulnerability analysis of interdependent critical infrastructures: case study of the Swedish railway system , 2011, Int. J. Crit. Infrastructures.

[7]  Tom Petersen,et al.  Importance and Exposure in Road Network Vulnerability Analysis , 2006 .

[8]  Wenli Li,et al.  An information granulation entropy-based model for third-party logistics providers evaluation , 2012 .

[9]  R. Bolado,et al.  Comparing Ordered Weighted Averaging (OWA) and Copeland score for composite indicators in the field of security of energy supply , 2011 .

[10]  Fatih Emre Boran,et al.  The Evaluation of Renewable Energy Technologies for Electricity Generation in Turkey Using Intuitionistic Fuzzy TOPSIS , 2012 .

[11]  Drakoulis Martakos,et al.  A utility-based fuzzy TOPSIS method for energy efficient network selection in heterogeneous wireless networks , 2012, Appl. Soft Comput..

[12]  Gyutai Kim,et al.  Identifying investment opportunities for advanced manufacturing systems with comparative-integrated performance measurement , 1997 .

[13]  Andrew V. Goldberg,et al.  A new approach to the maximum flow problem , 1986, STOC '86.

[14]  Mahdi Bashiri,et al.  A goal programming-TOPSIS approach to multiple response optimization using the concepts of non-dominated solutions and prediction intervals , 2011, Expert Syst. Appl..

[15]  Massimo Marchiori,et al.  Vulnerability and protection of infrastructure networks. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[16]  Matthias Ehrgott,et al.  Multiple criteria decision analysis: state of the art surveys , 2005 .

[17]  S. Mahadevan,et al.  A new method of identifying influential nodes in complex networks based on TOPSIS , 2014 .

[18]  Richard L. Church,et al.  Analysis of Facility Systems’ Reliability When Subject to Attack or a Natural Disaster , 2007 .

[19]  Willi Hock,et al.  Lecture Notes in Economics and Mathematical Systems , 1981 .

[20]  Dulcy M. Abraham,et al.  Allocating security resources to a water supply network , 2007 .

[21]  P. Vincke,et al.  Note-A Preference Ranking Organisation Method: The PROMETHEE Method for Multiple Criteria Decision-Making , 1985 .

[22]  Juan Carlos García-Palomares,et al.  Measuring the vulnerability of public transport networks , 2014 .

[23]  José Rui Figueira,et al.  The SMAA-PROMETHEE method , 2014, Eur. J. Oper. Res..

[24]  Alan T. Murray,et al.  A Methodological Overview of Network Vulnerability Analysis , 2008 .

[25]  Juan Carlos Ruiz,et al.  Assessing the importance of components in a system modeled as a network , 2012 .

[26]  Hanif D. Sherali,et al.  Linear Programming and Network Flows , 1977 .

[27]  Morteza Yazdani,et al.  A state-of the-art survey of TOPSIS applications , 2012, Expert Syst. Appl..

[28]  P. Suarez,et al.  Impacts of flooding and climate change on urban transportation: A systemwide performance assessment of the Boston Metro Area , 2005 .

[29]  F. Lootsma.  Multi-Criteria Decision Analysis via Ratio and Difference Judgement , 1999 .

[30]  Bertrand Mareschal,et al.  Prométhée: a new family of outranking methods in multicriteria analysis , 1984 .

[31]  Helmut Viernstein,et al.  Comprehensive evaluation of natural antioxidants and antioxidant potentials in Ziziphus jujuba Mill. var. spinosa (Bunge) Hu ex H. F. Chou fruits based on geographical origin by TOPSIS method , 2011 .

[32]  Igor Mishkovski,et al.  Vulnerability of complex networks , 2011 .

[33]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[34]  Thomas L. Saaty,et al.  DECISION MAKING WITH THE ANALYTIC HIERARCHY PROCESS , 2008 .

[35]  Kash Barker,et al.  Interval-valued availability framework for supplier selection based on component importance , 2015 .

[36]  Kay W. Axhausen,et al.  Vulnerability Assessment Methodology for Swiss Road Network , 2009 .

[37]  Serge Domenech,et al.  A multiobjective optimization framework for multicontaminant industrial water network design. , 2011, Journal of environmental management.

[38]  David L. Olson,et al.  Comparison of weights in TOPSIS models , 2004, Math. Comput. Model..

[39]  H Jönsson,et al.  Identifying critical components in technical infrastructure networks , 2008 .

[40]  Frederick S. Hillier,et al.  Introduction of Operations Research , 1967 .

[41]  Qiang Qiang,et al.  A network efficiency measure with application to critical infrastructure networks , 2008, J. Glob. Optim..

[42]  S. P. Sivapirakasam,et al.  Multi-attribute decision making for green electrical discharge machining , 2011, Expert Syst. Appl..

[43]  Tommi Tervonen,et al.  Implementing stochastic multicriteria acceptability analysis , 2007, Eur. J. Oper. Res..

[44]  Anthony Chen,et al.  Network-based Accessibility Measures for Vulnerability Analysis of Degradable Transportation Networks , 2007 .

[45]  Taho Yang,et al.  A lean pull system design analysed by value stream mapping and multiple criteria decision-making method under demand uncertainty , 2011, Int. J. Comput. Integr. Manuf..

[46]  M. S. García-Cascales,et al.  Decision support in disinfection technologies for treated wastewater reuse , 2009 .

[47]  Gang Kou,et al.  An empirical study of classification algorithm evaluation for financial risk prediction , 2011, Appl. Soft Comput..

[48]  Ghanima Al-Sharrah,et al.  Ranking Using the Copeland Score: A Comparison with the Hasse Diagram , 2010, J. Chem. Inf. Model..

[49]  Emel Kizilkaya Aydogan,et al.  Performance measurement model for Turkish aviation firms using the rough-AHP and TOPSIS methods under fuzzy environment , 2011, Expert Syst. Appl..

[50]  Claudio M. Rocco,et al.  A Non-Parametric Aggregation Technique for Identifying Critical Nodes in a Network, using Three Topology-Based Cascade Models , 2014 .

[51]  Alan T. Murray,et al.  Critical network infrastructure analysis: interdiction and system flow , 2007, J. Geogr. Syst..

[52]  Jean Pierre Brans,et al.  A PREFERENCE RANKING ORGANIZATION METHOD , 1985 .

[53]  James H. Lambert,et al.  Terrorism Scenario Identification by Superposition of Infrastructure Networks , 2005 .

[54]  Cathy Macharis,et al.  THE APPLICABILITY OF MULTICRITERIA-ANALYSIS TO THE EVALUATION OF INTELLIGENT TRANSPORT SYSTEMS (ITS). IN: ECONOMIC IMPACTS OF INTELLIGENT TRANSPORTATION SYSTEMS: INNOVATIONS AND CASE STUDIES , 2004 .

[55]  Hüseyin Uzunalioglu,et al.  A network survivability model for critical national infrastructures , 2004, Bell Labs Technical Journal.

[56]  C. Yeh.  A Problem‐based Selection of Multi‐attribute Decision‐making Methods , 2002 .

[57]  Diyar Akay,et al.  Personnel selection based on intuitionistic fuzzy sets , 2011 .

[58]  Darren M. Scott,et al.  Identifying Critical Road Segments and Measuring System-Wide Robustness in Transportation Networks with Isolating Links: A Link-Based Capacity-Reduction Approach , 2010 .

[59]  H. Kunzi,et al.  Lectu re Notes in Economics and Mathematical Systems , 1975 .

[60]  Enrico Zio,et al.  Reliability and vulnerability analyses of critical infrastructures: Comparing two approaches in the context of power systems , 2013, Reliab. Eng. Syst. Saf..

[61]  Sifeng Liu,et al.  An OWA-TOPSIS method for multiple criteria decision analysis , 2011, Expert Syst. Appl..

[62]  Kash Barker,et al.  Flow-based vulnerability measures for network component importance: Experimentation with preparedness planning , 2016, Reliab. Eng. Syst. Saf..

[63]  P. Legendre.  Species associations: the Kendall coefficient of concordance revisited , 2005 .