Solving Civil Engineering Problems by Means of Fuzzy and Stochastic MCDM Methods: Current State and Future Research

The present review examines decision-making methods developed for dealing with uncertainties and applied to solve problems of civil engineering. Several methodological difficulties emerging from uncertainty quantification in decision-making are identified. The review is focused on formal methods of multiple criteria decision-making (MCDM). Handling of uncertainty by means of fuzzy logic and probabilistic modelling is analysed in light of MCDM. A sensitivity analysis of MCDM problems with uncertainties is discussed. An application of stochastic MCDM methods to a design of safety critical objects of civil engineering is considered. Prospects of using MCDM under uncertainty in developing areas of civil engineering are discussed in brief. These areas are design of sustainable and energy efficient buildings, building information modelling, and assurance of security and safety of built property. It is stated that before long the decision-making in civil engineering may face several methodological problems: the need to combine fuzzy and probabilistic representations of uncertainties in one decision-making matrix, the necessity to extend a global sensitivity analysis to all input elements of a MCDM problem with uncertainties, and an application of MCDM methods in the areas of civil engineering where decision-making under uncertainty is presently not common.

[1]  Cengiz Kahraman,et al.  Fuzzy Multicriteria Decision-Making: A Literature Review , 2015, Int. J. Comput. Intell. Syst..

[2]  S. Chanas.  The use of parametric programming in fuzzy linear programming , 1983 .

[3]  Safak Kiris,et al.  Multi-Criteria Inventory Classification by Using a Fuzzy Analytic Network Process (ANP) Approach , 2013, Informatica.

[4]  Zhi-Hui Li,et al.  An Extension of the MULTIMOORA Method for Multiple Criteria Group Decision Making Based upon Hesitant Fuzzy Sets , 2014, J. Appl. Math..

[5]  Egidijus Rytas Vaidogas,et al.  Multi-attribute Decision-making in Economics of Fire Protection , 2011 .

[6]  E. Zavadskas,et al.  A complex proportional assessment method for group decision making in an interval-valued intuitionistic fuzzy environment , 2013 .

[7]  Sunil K. Sinha,et al.  Resilience of civil infrastructure systems: literature review for improved asset management , 2013, Int. J. Crit. Infrastructures.

[8]  H. Pasman.  Loss prevention in the process industries , 2002 .

[9]  Edmundas Kazimieras Zavadskas,et al.  Environmental impact assessment based on group decision-making methods in mining projects , 2014 .

[10]  Hu-Chen Liu,et al.  Evaluating the risk of failure modes with extended MULTIMOORA method under fuzzy environment , 2014, Eng. Appl. Artif. Intell..

[11]  Siuming Lo,et al.  A simulation approach for ranking of fire safety attributes of existing buildings , 2004 .

[12]  James Nga-Kwok Liu,et al.  Application of decision-making techniques in supplier selection: A systematic review of literature , 2013, Expert Syst. Appl..

[13]  Huishan Wu,et al.  A novel framework to evaluate programmable logic controllers: a fuzzy MCDM perspective , 2016, J. Intell. Manuf..

[14]  B. John Garrick,et al.  Quantifying and Controlling Catastrophic Risks , 2008 .

[15]  Ana Nieto-Morote,et al.  A fuzzy multi-criteria decision making model for construction contractor prequalification , 2012 .

[16]  A. Shanian,et al.  A methodological concept for material selection of highly sensitive components based on multiple criteria decision analysis , 2009, Expert Syst. Appl..

[17]  Mahdi Zarghami,et al.  On the relation between Compromise Programming and Ordered Weighted Averaging operator , 2010, Inf. Sci..

[18]  Ying Luo,et al.  Integration of correlations with standard deviations for determining attribute weights in multiple attribute decision making , 2010, Math. Comput. Model..

[19]  Wei Zhang,et al.  Fuzzy Analytic Hierarchy Process Synthetic Evaluation Models for the Health Monitoring of Shield Tunnels , 2014, Comput. Aided Civ. Infrastructure Eng..

[20]  Robert LIN,et al.  NOTE ON FUZZY SETS , 2014 .

[21]  Marcello Braglia,et al.  The analytic hierarchy process applied to maintenance strategy selection , 2000, Reliab. Eng. Syst. Saf..

[22]  Johnny Wong,et al.  Evaluating the system intelligence of the intelligent building systems : Part 1 : Development of key intelligent indicators and conceptual analytical framework , 2008 .

[23]  Claus Rinner,et al.  Advances in Geographic Information Science , 2015 .

[24]  Anjali Awasthi,et al.  Application of fuzzy TOPSIS in evaluating sustainable transportation systems , 2011, Expert Syst. Appl..

[25]  Solomon Tesfamariam,et al.  A review of multi-criteria decision-making methods for infrastructure management , 2014 .

[26]  Stefano Tarantola,et al.  Uncertainty and sensitivity analysis techniques as tools for the quality assessment of composite indicators , 2005 .

[27]  Egidijus Rytas Vaidogas,et al.  Protecting built property against fire disasters: Multi ‐attribute decision making with respect to fire risk , 2010 .

[28]  Tomas Baležentis,et al.  A Survey on Development and Applications of the Multi‐criteria Decision Making Method MULTIMOORA , 2014 .

[29]  M. Law,et al.  Evaluation of Fire Safety: Rasbash/Evaluation of Fire Safety , 2006 .

[30]  Eglė Šiožinytė,et al.  Upgrading the old vernacular building to contemporary norms: multiple criteria approach , 2014 .

[31]  Reza Baradaran Kazemzadeh,et al.  PROMETHEE: A comprehensive literature review on methodologies and applications , 2010, Eur. J. Oper. Res..

[32]  Ravi Shankar,et al.  An STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: A case study from India , 2012 .

[33]  David Ben-Arieh.  Sensitivity of multi-criteria decision making to linguistic quantifiers and aggregation means , 2005, Comput. Ind. Eng..

[34]  Andrew R.J. Dainty,et al.  Sustainability and resilience in the built environment: The challenges of establishing a turquoise agenda in the UK , 2015 .

[35]  Mahdi Zarghami,et al.  Soft computing of the Borda count by fuzzy linguistic quantifiers , 2009, Appl. Soft Comput..

[36]  Hu-Chen Liu,et al.  Application of interval 2-tuple linguistic MULTIMOORA method for health-care waste treatment technology evaluation and selection. , 2014, Waste management.

[37]  Edmundas Kazimieras Zavadskas,et al.  Introducing reliability measures into multi-criteria decision-making , 2007 .

[38]  Evangelos Triantaphyllou,et al.  An examination of the effectiveness of multi-dimensional decision-making methods: A decision-making paradox , 1989, Decis. Support Syst..

[39]  Xiaohong Chen,et al.  Stochastic multiple criteria decision making with aspiration level based on prospect stochastic dominance , 2014, Knowl. Based Syst..

[40]  Daniel Jato-Espino,et al.  A review of application of multi-criteria decision making methods in construction , 2014 .

[41]  Jolanta Tamošaitienė,et al.  COMPLEX ASSESSMENT OF STRUCTURAL SYSTEMS USED FOR HIGH-RISE BUILDINGS , 2013 .

[42]  S. K. Goyal,et al.  A multi-criteria decision making approach for location planning for urban distribution centers under uncertainty , 2011, Math. Comput. Model..

[43]  Rajeev Jain,et al.  A Fuzzy AHP and PROMETHEE method-based heuristic for disassembly line balancing problems , 2014 .

[44]  Anjali Awasthi,et al.  A hybrid approach integrating Affinity Diagram, AHP and fuzzy TOPSIS for sustainable city logistics planning , 2012 .

[45]  Vladimir Rykov.  Reliability and Risk , 2016 .

[46]  Chao Fu,et al.  An interval difference based evidential reasoning approach with unknown attribute weights and utilities of assessment grades , 2015, Comput. Ind. Eng..

[47]  Egidijus Rytas Vaidogas,et al.  Sitting the barrier aimed at protecting roadside property from accidental fires and explosions on road: a pre-optimisation stage , 2012 .

[48]  Dag Eirik Nordgård,et al.  Integrating risk analysis and multi-criteria decision support under uncertainty in electricity distribution system asset management , 2011, Reliab. Eng. Syst. Saf..

[49]  E. Triantaphyllou,et al.  A Sensitivity Analysis Approach for Some Deterministic Multi-Criteria Decision-Making Methods* , 1997 .

[50]  Keqian Zhang,et al.  Risk analysis and management of submerged floating tunnel and its application , 2010 .

[51]  E. Zavadskas,et al.  A new fuzzy additive ratio assessment method (ARAS‐F). Case study: The analysis of fuzzy multiple criteria in order to select the logistic centers location , 2010 .

[52]  Arika Ligmann-Zielinska,et al.  Spatially-explicit sensitivity analysis of an agent-based model of land use change , 2013, Int. J. Geogr. Inf. Sci..

[53]  Jens Leth Hougaard,et al.  Fuzzy efficiency without convexity , 2014, Fuzzy Sets Syst..

[54]  Eric D. Vugrin,et al.  Resilience certification for commercial buildings: a study of stakeholder perspectives , 2013, Environment Systems and Decisions.

[55]  Luis G. Vargas.  Reciprocal matrices with random coefficients , 1982 .

[56]  Jiangjiang Wang,et al.  Review on multi-criteria decision analysis aid in sustainable energy decision-making , 2009 .

[57]  Reza Tavakkoli-Moghaddam,et al.  Soft computing based on a fuzzy grey group compromise solution approach with an application to the selection problem of material handling equipment , 2014, Int. J. Comput. Integr. Manuf..

[58]  Edmundas Kazimieras Zavadskas,et al.  State of art surveys of overviews on MCDM/MADM methods , 2014 .

[59]  Jurgita Antucheviciene,et al.  Extension of weighted aggregated sum product assessment with interval-valued intuitionistic fuzzy numbers (WASPAS-IVIF) , 2014, Appl. Soft Comput..

[60]  Jian Ren,et al.  Multiple Criteria Decision Making Based on Discrete Linguistic Stochastic Variables , 2013 .

[61]  Jurgita Antucheviciene,et al.  Multiple criteria evaluation of rural building's regeneration alternatives , 2007 .

[62]  S. Rahman.  Reliability Engineering and System Safety , 2011 .

[63]  Maghsoud Amiri,et al.  Multiple criteria group decision-making for supplier selection based on COPRAS method with interval type-2 fuzzy sets , 2014, The International Journal of Advanced Manufacturing Technology.

[64]  Lotfi A. Zadeh,et al.  Fuzzy Set Theory and Probability Theory: What is the Relationship? , 2011, International Encyclopedia of Statistical Science.

[65]  Matthias C. M. Troffaes,et al.  A robust Bayesian approach to modeling epistemic uncertainty in common-cause failure models , 2013, Reliab. Eng. Syst. Saf..

[66]  Edmundas Kazimieras Zavadskas,et al.  Multi-criteria selection of a deep-water port in the Eastern Baltic Sea , 2015, Appl. Soft Comput..

[67]  Ana Nieto-Morote,et al.  A fuzzy approach to construction project risk assessment , 2011 .

[68]  Anjali Awasthi,et al.  A hybrid approach based on SERVQUAL and fuzzy TOPSIS for evaluating transportation service quality , 2011, Comput. Ind. Eng..

[69]  Johnny Wong,et al.  Evaluating the system intelligence of the intelligent building systems: Part 2: Construction and validation of analytical models , 2008 .

[70]  Abdollah Hadi-Vencheh,et al.  A new hybrid fuzzy multi-criteria decision making model for solving the material handling equipment selection problem , 2015, Int. J. Comput. Integr. Manuf..

[71]  Jon C. Helton,et al.  Alternative representations of epistemic uncertainty , 2004, Reliab. Eng. Syst. Saf..

[72]  K. Wong,et al.  Sustainable supplier selection and order lot-sizing: an integrated multi-objective decision-making process , 2015 .

[73]  Jurgita Antucheviciene,et al.  Applying fuzzy MCDM for financial performance evaluation of Iranian companies , 2014 .

[74]  Niamh Nic Daeid,et al.  Fires and related incidents in Dubai, United Arab Emirates (2006-2013) , 2014 .

[75]  Chin-Tsai Lin,et al.  An application of AHP and sensitivity analysis for selecting the best slicing machine , 2007, Comput. Ind. Eng..

[76]  M. Rausand.  Reliability of Safety-Critical Systems: Theory and Applications , 2014 .

[77]  Gülçin Büyüközkan,et al.  A combined fuzzy AHP and fuzzy TOPSIS based strategic analysis of electronic service quality in healthcare industry , 2012, Expert Syst. Appl..

[78]  Curtis L. Smith,et al.  Bayesian Inference for Probabilistic Risk Assessment: A Practitioner's Guidebook , 2011 .

[79]  W. Pedrycz,et al.  A fuzzy extension of Saaty's priority theory , 1983 .

[80]  Edmundas K. Zavadskas,et al.  Multiattribute Selection from Alternative Designs of Infrastructure Components for Accidental Situations , 2009, Comput. Aided Civ. Infrastructure Eng..

[81]  Edmundas Kazimieras Zavadskas,et al.  Reliability measures in multicriteria decision making as applied to engineering projects , 2007 .

[82]  Bijan Sarkar,et al.  Selection of robot for automated foundry operations using fuzzy multi-criteria decision making approaches , 2014 .

[83]  C. Kahraman.  Multi-Criteria Decision Making Methods and Fuzzy Sets , 2008 .

[84]  Zenonas Turskis,et al.  An integrated model for extending brand based on fuzzy ARAS and ANP methods , 2014 .

[85]  Jun Liu,et al.  An integrated AHP-DEA methodology for bridge risk assessment , 2008, Comput. Ind. Eng..

[86]  Christopher J. Roy,et al.  A comprehensive framework for verification, validation, and uncertainty quantification in scientific computing , 2011 .

[87]  Egidijus Rytas Vaidogas,et al.  ON APPLYING SPARSE AND UNCERTAIN INFORMATION TO ESTIMATING THE PROBABILITY OF FAILURE DUE TO RARE ABNORMAL SITUATIONS , 2009 .

[88]  Yao Zhang,et al.  A method based on stochastic dominance degrees for stochastic multiple criteria decision making , 2010, Comput. Ind. Eng..

[89]  Saltelli Andrea,et al.  Global Sensitivity Analysis: The Primer , 2008 .

[90]  Majid Behzadian,et al.  A fuzzy hybrid group decision support system approach for the supplier evaluation process , 2014 .

[91]  Anique Hommels,et al.  The EU Seveso regime in practice: from uncertainty blindness to uncertainty tolerance. , 2010, Journal of hazardous materials.

[92]  Jian-Xin You,et al.  Evaluating health-care waste treatment technologies using a hybrid multi-criteria decision making model , 2015 .

[93]  Rajeev Jain,et al.  A Kano model, AHP and M-TOPSIS method-based technique for disassembly line balancing under fuzzy environment , 2014, Appl. Soft Comput..

[94]  Gwo-Hshiung Tzeng,et al.  Comments on “Multiple criteria decision making (MCDM) methods in economics: an overview” , 2012 .

[95]  O. Tatari,et al.  Ranking the sustainability performance of pavements: An intuitionistic fuzzy decision making method , 2014 .

[96]  Cheng Wei Liao,et al.  Using a hybrid MCDM methodology to identify critical factors in new product development , 2012, Neural Computing and Applications.

[97]  Shouzhen Zeng,et al.  A Projection Method for Multiple Attribute Group Decision Making with Intuitionistic Fuzzy Information , 2013, Informatica.

[98]  Matthias Ehrgott,et al.  Multiple criteria decision making for engineering , 2008 .

[99]  Edmundas Kazimieras Zavadskas,et al.  Fuzzy multiple criteria decision-making techniques and applications - Two decades review from 1994 to 2014 , 2015, Expert Syst. Appl..

[100]  Liu Hui,et al.  Study on Safety Assessment of Fire Hazard for the Construction Site , 2012 .

[101]  Jian-Lan Zhou,et al.  A hybrid approach for safety assessment in high-risk hydropower-construction-project work systems , 2014 .

[102]  Gülçin Büyüközkan,et al.  A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information , 2011, Comput. Ind..

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

[104]  Tarek Zayed,et al.  Contractor Selection Model for Highway Projects Using Integrated Simulation and Analytic Network Process , 2013 .

[105]  Chin-Tsai Lin,et al.  Optimal Selection of Location for Taiwanese Hospitals to Ensure a Competitive Advantage by Using the Analytic Hierarchy Process and Sensitivity Analysis , 2007 .

[106]  Serhat Burmaoglu,et al.  A fuzzy multi-criteria decision making approach to assess building energy performance , 2014 .

[107]  Richard J. Beckman,et al.  A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code , 2000, Technometrics.

[108]  Uwe Reuter,et al.  Uncertainty Forecasting in Engineering , 2007 .

[109]  L. Anojkumar,et al.  Comparative analysis of MCDM methods for pipe material selection in sugar industry , 2014, Expert Syst. Appl..

[110]  Enrique Herrera-Viedma,et al.  Managing incomplete preference relations in decision making: A review and future trends , 2015, Inf. Sci..

[111]  T. L. Saaty.  A Scaling Method for Priorities in Hierarchical Structures , 1977 .

[112]  Ronald L. Iman,et al.  Risk methodology for geologic disposal of radioactive waste: small sample sensitivity analysis techniques for computer models, with an application to risk assessment , 1980 .

[113]  Shouzhen Zeng,et al.  MULTIMOORA-IFN: A mcdm method based on intuitionistic fuzzy number for performance management , 2015 .

[114]  Ünal Kurt,et al.  The fuzzy TOPSIS and generalized Choquet fuzzy integral algorithm for nuclear power plant site selection – a case study from Turkey , 2014 .

[115]  Arika Ligmann-Zielinska,et al.  Spatially-explicit integrated uncertainty and sensitivity analysis of criteria weights in multicriteria land suitability evaluation , 2014, Environ. Model. Softw..