Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2015, Article ID 362579, 16 pages
http://dx.doi.org/10.1155/2015/362579
Review Article

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

1Department of Construction Technology and Management, Faculty of Civil Engineering, Vilnius Gediminas Technical University, Saulėtekio Alėja 11, LT-10223 Vilnius, Lithuania
2Department of Structural Mechanics, Faculty of Civil Engineering, Brno University of Technology, Veveří Street 95, 602 00 Brno, Czech Republic
3Department of Structural Engineering, Faculty of Engineering, Cairo University, Giza 12613, Egypt
4Department of Labour Safety and Fire Protection, Faculty of Civil Engineering, Vilnius Gediminas Technical University, Saulėtekio Alėja 11, LT-10223 Vilnius, Lithuania

Received 9 May 2015; Accepted 11 June 2015

Academic Editor: Peide Liu

Copyright © 2015 Jurgita Antucheviciene et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. M. M. Wiecek, M. Ehrgott, G. Fadel, and J. R. Figueira, “Multiple criteria decision making for engineering,” Omega, vol. 36, no. 3, pp. 337–339, 2008. View at Publisher · View at Google Scholar · View at Scopus
  2. A. Mardani, A. Jusoh, and E. K. Zavadskas, “Fuzzy multiple criteria decision-making techniques and applications—two decades review from 1994 to 2014,” Expert Systems with Applications, vol. 42, no. 8, pp. 4126–4148, 2015. View at Publisher · View at Google Scholar · View at Scopus
  3. J. J. H. Liou and G.-H. Tzeng, “Comments on ‘Multiple criteria decision making (MCDM) methods in economics: an overview’,” Technological and Economic Development of Economy, vol. 18, no. 4, pp. 672–695, 2012. View at Publisher · View at Google Scholar · View at Scopus
  4. E. K. Zavadskas, Z. Turskis, and S. Kildiene, “State of art surveys of overviews on MCDM/MADM methods,” Technological and Economic Development of Economy, vol. 20, no. 1, pp. 165–179, 2014. View at Publisher · View at Google Scholar · View at Scopus
  5. T. Baležentis and A. Baležentis, “A survey on development and applications of the multi-criteria decision making method MULTIMOORA,” Journal of Multi-Criteria Decision Analysis, vol. 21, no. 3-4, pp. 209–222, 2014. View at Publisher · View at Google Scholar · View at Scopus
  6. M. Behzadian, R. B. Kazemzadeh, A. Albadvi, and M. Aghdasi, “PROMETHEE: a comprehensive literature review on methodologies and applications,” European Journal of Operational Research, vol. 200, no. 1, pp. 198–215, 2010. View at Publisher · View at Google Scholar · View at Scopus
  7. M. Behzadian, S. Khanmohammadi Otaghsara, M. Yazdani, and J. Ignatius, “A state-of the-art survey of TOPSIS applications,” Expert Systems with Applications, vol. 39, no. 17, pp. 13051–13069, 2012. View at Publisher · View at Google Scholar · View at Scopus
  8. R. Ureña, F. Chiclana, J. A. Morente-Molinera, and E. Herrera-Viedma, “Managing incomplete preference relations in decision making: a review and future trends,” Information Sciences, vol. 302, no. 1, pp. 14–32, 2015. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  9. J. Chai, J. N. K. Liu, and E. W. T. Ngai, “Application of decision-making techniques in supplier selection: a systematic review of literature,” Expert Systems with Applications, vol. 40, no. 10, pp. 3872–3885, 2013. View at Publisher · View at Google Scholar · View at Scopus
  10. G. Kabir, R. Sadiq, and S. Tesfamariam, “A review of multi-criteria decision-making methods for infrastructure management,” Structure and Infrastructure Engineering: Maintenance, Management, Life-Cycle Design and Performance, vol. 10, no. 9, pp. 1176–1210, 2014. View at Publisher · View at Google Scholar · View at Scopus
  11. D. Jato-Espino, E. Castillo-Lopez, J. Rodriguez-Hernandez, and J. C. Canteras-Jordana, “A review of application of multi-criteria decision making methods in construction,” Automation in Construction, vol. 45, pp. 151–162, 2014. View at Publisher · View at Google Scholar · View at Scopus
  12. C. Kahraman, “Multi-criteria decision making methods and fuzzy sets,” in Fuzzy Multi-Criteria Decision Making, C. Kahraman, Ed., vol. 16 of Springer Optimization and Its Applications, pp. 1–18, Springer, New York, NY, USA, 2008. View at Publisher · View at Google Scholar
  13. J. Tamošaitiene and E. Gaudutis, “Complex assessment of structural systems used for high-rise buildings,” Journal of Civil Engineering and Management, vol. 19, no. 2, pp. 305–317, 2013. View at Publisher · View at Google Scholar · View at Scopus
  14. E. Šiožinyte, J. Antuchevičiene, and V. Kutut, “Upgrading the old vernacular building to contemporary norms: multiple criteria approach,” Journal of Civil Engineering and Management, vol. 20, no. 2, pp. 291–298, 2014. View at Publisher · View at Google Scholar · View at Scopus
  15. J. L. Hougaard and T. Baležentis, “Fuzzy efficiency without convexity,” Fuzzy Sets and Systems, vol. 255, pp. 17–29, 2014. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  16. L. A. Zadeh, “Fuzzy set theory and probability theory: what is the relationship?” in International Encyclopedia of Statistical Science, pp. 563–566, Springer, 2014. View at Google Scholar
  17. D. Kelly and C. Smith, Bayesian Inference for Probabilistic Risk Assessment: A Practitioner's Guidebook, Springer, New York, NY, USA, 2011.
  18. J.-J. Wang, Y.-Y. Jing, C.-F. Zhang, and J.-H. Zhao, “Review on multi-criteria decision analysis aid in sustainable energy decision-making,” Renewable and Sustainable Energy Reviews, vol. 13, no. 9, pp. 2263–2278, 2009. View at Publisher · View at Google Scholar · View at Scopus
  19. Y.-M. Wang and Y. Luo, “Integration of correlations with standard deviations for determining attribute weights in multiple attribute decision making,” Mathematical and Computer Modelling, vol. 51, no. 1-2, pp. 1–12, 2010. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  20. C. Fu and Y. Wang, “An interval difference based evidential reasoning approach with unknown attribute weights and utilities of assessment grades,” Computers and Industrial Engineering, vol. 81, pp. 109–117, 2015. View at Publisher · View at Google Scholar · View at Scopus
  21. E. Triantaphyllou and S. H. Mann, “An examination of the effectiveness of multi-dimensional decision-making methods: a decision-making paradox,” International Journal of Decision Support Systems, vol. 5, no. 3, pp. 303–312, 1989. View at Publisher · View at Google Scholar · View at Scopus
  22. L. A. Zadeh, “Fuzzy sets,” Information and Control, vol. 8, no. 3, pp. 338–353, 1965. View at Google Scholar
  23. P. J. M. van Laarhoven and W. Pedrycz, “A fuzzy extension of Saaty's priority theory,” Fuzzy Sets and Systems, vol. 11, no. 3, pp. 229–241, 1983. View at Publisher · View at Google Scholar · View at MathSciNet
  24. C. Kahraman, S. C. Onar, and B. Oztaysi, “Fuzzy multicriteria decision-making: a literature review,” International Journal of Computational Intelligence Systems, vol. 8, no. 4, pp. 637–666, 2015. View at Publisher · View at Google Scholar
  25. E. K. Zavadskas, J. Antucheviciene, S. H. R. Hajiagha, and S. S. Hashemi, “Extension of weighted aggregated sum product assessment with interval-valued intuitionistic fuzzy numbers (WASPAS-IVIF),” Applied Soft Computing, vol. 24, pp. 1013–1021, 2014. View at Publisher · View at Google Scholar · View at Scopus
  26. S. H. Razavi Hajiagha, S. S. Hashemi, and E. K. Zavadskas, “A complex proportional assessment method for group decision making in an interval-valued intuitionistic fuzzy environment,” Technological and Economic Development of Economy, vol. 19, no. 1, pp. 22–37, 2013. View at Publisher · View at Google Scholar · View at Scopus
  27. H.-C. Liu, X.-J. Fan, P. Li, and Y.-Z. Chen, “Evaluating the risk of failure modes with extended MULTIMOORA method under fuzzy environment,” Engineering Applications of Artificial Intelligence, vol. 34, pp. 168–177, 2014. View at Publisher · View at Google Scholar · View at Scopus
  28. H.-C. Liu, J.-X. You, C. Lu, and Y.-Z. Chen, “Evaluating health-care waste treatment technologies using a hybrid multi-criteria decision making model,” Renewable and Sustainable Energy Reviews, vol. 41, pp. 932–942, 2015. View at Publisher · View at Google Scholar · View at Scopus
  29. H.-C. Liu, J.-X. You, Ch. Lu, and M.-M. Shan, “Application of interval 2-tuple linguistic MULTIMOORA method for health-care waste treatment technology evaluation and selection,” Waste Management, vol. 34, no. 11, pp. 2355–2364, 2014. View at Publisher · View at Google Scholar · View at Scopus
  30. T. Balezentis, S. Z. Zeng, and A. Balezentis, “MULTIMOORA-IFN: a MCDM method based on intuitionistic fuzzy number for performance management,” Economic Computation and Economic Cybernetics Studies and Research, vol. 48, no. 4, pp. 85–102, 2014. View at Google Scholar
  31. Z.-H. Li, “An extension of the MULTIMOORA method for multiple criteria group decision making based upon hesitant fuzzy sets,” Journal of Applied Mathematics, vol. 2014, Article ID 527836, 16 pages, 2014. View at Publisher · View at Google Scholar · View at Scopus
  32. Z. Turskis and E. K. Zavadskas, “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,” Transport, vol. 25, no. 4, pp. 423–432, 2010. View at Publisher · View at Google Scholar · View at Scopus
  33. M. Zamani, A. Rabbani, A. Yazdani-Chamzini, and Z. Turskis, “An integrated model for extending brand based on fuzzy ARAS and ANP methods,” Journal of Business Economics and Management, vol. 15, no. 3, pp. 403–423, 2014. View at Publisher · View at Google Scholar · View at Scopus
  34. A. S. Ghadikolaei, S. K. Esbouei, and J. Antucheviciene, “Applying fuzzy MCDM for financial performance evaluation of Iranian companies,” Technological and Economic Development of Economy, vol. 20, no. 2, pp. 274–291, 2014. View at Publisher · View at Google Scholar
  35. N. Rikhtegar, N. Mansouri, A. A. Oroumieh, A. Yazdani-Chamzini, E. K. Zavadskas, and S. Kildienė, “Environmental impact assessment based on group decision-making methods in mining projects,” Economic Research-Ekonomska Istraživanja, vol. 27, no. 1, pp. 378–392, 2014. View at Publisher · View at Google Scholar
  36. M. Kabak, E. Köse, O. Kirilmaz, and S. Burmaoğlu, “A fuzzy multi-criteria decision making approach to assess building energy performance,” Energy and Buildings, vol. 72, pp. 382–389, 2014. View at Publisher · View at Google Scholar · View at Scopus
  37. M. Kucukvar, S. Gumus, G. Egilmez, and O. Tatari, “Ranking the sustainability performance of pavements: an intuitionistic fuzzy decision making method,” Automation in Construction, vol. 40, pp. 33–43, 2014. View at Publisher · View at Google Scholar · View at Scopus
  38. A. H. Azadnia, M. Z. M. Saman, and K. Y. Wong, “Sustainable supplier selection and order lot-sizing: an integrated multi-objective decision-making process,” International Journal of Production Research, vol. 53, no. 2, pp. 383–408, 2015. View at Publisher · View at Google Scholar · View at Scopus
  39. S. M. Hashemian, M. Behzadian, R. Samizadeh, and J. Ignatius, “A fuzzy hybrid group decision support system approach for the supplier evaluation process,” The International Journal of Advanced Manufacturing Technology, vol. 73, no. 5–8, pp. 1105–1117, 2014. View at Publisher · View at Google Scholar · View at Scopus
  40. M. K. Ghorabaee, M. Amiri, J. S. Sadaghiani, and G. H. Goodarzi, “Multiple criteria group decision-making for supplier selection based on COPRAS method with interval type-2 fuzzy sets,” The International Journal of Advanced Manufacturing Technology, vol. 75, no. 5–8, pp. 1115–1130, 2014. View at Publisher · View at Google Scholar · View at Scopus
  41. S. Zeng, T. Balezentis, J. Chen, and G. Luo, “A projection method for multiple attribute group decision making with intuitionistic fuzzy information,” Informatica, vol. 24, no. 3, pp. 485–503, 2013. View at Google Scholar · View at MathSciNet
  42. S. M. Mousavi, B. Vahdani, R. Tavakkoli-Moghaddam, and N. Tajik, “Soft computing based on a fuzzy grey group compromise solution approach with an application to the selection problem of material handling equipment,” International Journal of Computer Integrated Manufacturing, vol. 27, no. 6, pp. 547–569, 2014. View at Publisher · View at Google Scholar · View at Scopus
  43. A. Hadi-Vencheh and A. Mohamadghasemi, “A new hybrid fuzzy multi-criteria decision making model for solving the material handling equipment selection problem,” International Journal of Computer Integrated Manufacturing, vol. 28, no. 5, pp. 534–550, 2015. View at Publisher · View at Google Scholar · View at Scopus
  44. S. Kiris, “Multi-criteria inventory classification by using a fuzzy analytic network process (ANP) approach,” Informatica, vol. 24, no. 2, pp. 199–217, 2013. View at Google Scholar
  45. B. Bairagi, B. Dey, B. Sarkar, and S. Sanyal, “Selection of robot for automated foundry operations using fuzzy multi-criteria decision making approaches,” International Journal of Management Science and Engineering Management, vol. 9, no. 3, pp. 221–232, 2014. View at Publisher · View at Google Scholar
  46. Ü. Kurt, “The fuzzy TOPSIS and generalized Choquet fuzzy integral algorithm for nuclear power plant site selection—a case study from Turkey,” Journal of Nuclear Science and Technology, vol. 51, no. 10, pp. 1241–1255, 2014. View at Publisher · View at Google Scholar · View at Scopus
  47. E. K. Zavadskas, Z. Turskis, and V. Bagočius, “Multi-criteria selection of a deep-water port in the Eastern Baltic Sea,” Applied Soft Computing Journal, vol. 26, pp. 180–192, 2014. View at Publisher · View at Google Scholar · View at Scopus
  48. W. Zhang, K. Sun, C. Lei, Y. Zhang, H. Li, and B. F. Spencer, “Fuzzy analytic hierarchy process synthetic evaluation models for the health monitoring of shield tunnels,” Computer-Aided Civil and Infrastructure Engineering, vol. 29, no. 9, pp. 676–688, 2014. View at Publisher · View at Google Scholar · View at Scopus
  49. S. Avikal, R. Jain, and P. K. Mishra, “A Kano model, AHP and M-TOPSIS method-based technique for disassembly line balancing under fuzzy environment,” Applied Soft Computing Journal, vol. 25, pp. 519–529, 2014. View at Publisher · View at Google Scholar · View at Scopus
  50. S. Avikal, P. K. Mishra, and R. Jain, “A fuzzy AHP and PROMETHEE method-based heuristic for disassembly line balancing problems,” International Journal of Production Research, vol. 52, no. 5, pp. 1306–1317, 2014. View at Publisher · View at Google Scholar · View at Scopus
  51. C. H. Wang and H. S. Wu, “A novel framework to evaluate programmable logic controllers: a fuzzy MCDM perspective,” Journal of Intelligent Manufacturing, 10 pages, 2014. View at Publisher · View at Google Scholar
  52. T.-M. Yeh, F.-Y. Pai, and C.-W. Liao, “Using a hybrid MCDM methodology to identify critical factors in new product development,” Neural Computing and Applications, vol. 24, no. 3-4, pp. 957–971, 2014. View at Publisher · View at Google Scholar · View at Scopus
  53. L. Anojkumar, M. Ilangkumaran, and V. Sasirekha, “Comparative analysis of MCDM methods for pipe material selection in sugar industry,” Expert Systems with Applications, vol. 41, no. 6, pp. 2964–2980, 2014. View at Publisher · View at Google Scholar · View at Scopus
  54. C. Tan, W. H. Ip, and X. Chen, “Stochastic multiple criteria decision making with aspiration level based on prospect stochastic dominance,” Knowledge-Based Systems, vol. 70, pp. 231–241, 2014. View at Publisher · View at Google Scholar · View at Scopus
  55. T. L. Saaty, “A scaling method for priorities in hierarchical structures,” Journal of Mathematical Psychology, vol. 15, no. 3, pp. 234–281, 1977. View at Google Scholar · View at MathSciNet
  56. L. G. Vargas, “Reciprocal matrices with random coefficients,” Mathematical Modelling, vol. 3, no. 1, pp. 69–81, 1982. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  57. A. Saltelli, K. Chan, and E. M. Scott, Sensitivity Analysis, Wiley Series in Probability and Statistics, John Wiley & Sons, New York, NY, USA, 2004.
  58. Y. Zhang, Z.-P. Fan, and Y. Liu, “A method based on stochastic dominance degrees for stochastic multiple criteria decision making,” Computers and Industrial Engineering, vol. 58, no. 4, pp. 544–552, 2010. View at Publisher · View at Google Scholar · View at Scopus
  59. J. Ren, Y. Gao, and C. Bian, “Multiple criteria decision making based on discrete linguistic stochastic variables,” Mathematical Problems in Engineering, vol. 2013, Article ID 546508, 11 pages, 2013. View at Publisher · View at Google Scholar · View at Scopus
  60. M. D. McKay, R. J. Beckman, and W. J. Conover, “A comparison of three methods for selecting values of input variables in the analysis of output from a computer code,” Technometrics, vol. 21, no. 2, pp. 239–245, 1979. View at Publisher · View at Google Scholar · View at MathSciNet
  61. R. L. Iman and W. J. Conover, “Small sample sensitivity analysis techniques for computer models with an application to risk assessment,” Communications in Statistics—Theory and Methods, vol. 9, no. 17, pp. 1749–1842, 1980. View at Publisher · View at Google Scholar · View at MathSciNet
  62. B. Möller and U. Reuter, Uncertainty Forecasting in Engineering, Springer, Berlin, Germany, 2007.
  63. A. Saltelli, M. Ratto, T. Andres et al., Global Sensitivity Analysis: the Primer, John Wiley & Sons, Chichester, UK, 2008. View at MathSciNet
  64. A. Saltelli, S. Tarantola, F. Campolongo, and M. Ratto, Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models, John Wiley & Sons, Chichester, UK, 2004. View at MathSciNet
  65. A. Ligmann-Zielinska, “Spatially-explicit sensitivity analysis of an agent-based model of land use change,” International Journal of Geographical Information Science, vol. 27, no. 9, pp. 1764–1781, 2013. View at Publisher · View at Google Scholar · View at Scopus
  66. A. Ligmann-Zielinska and P. Jankowski, “Spatially-explicit integrated uncertainty and sensitivity analysis of criteria weights in multicriteria land suitability evaluation,” Environmental Modelling & Software, vol. 57, pp. 235–247, 2014. View at Publisher · View at Google Scholar · View at Scopus
  67. C.-R. Wu, C.-T. Lin, and H.-C. Chen, “Optimal selection of location for Taiwanese hospitals to ensure a competitive advantage by using the analytic hierarchy process and sensitivity analysis,” Building and Environment, vol. 42, no. 3, pp. 1431–1444, 2007. View at Publisher · View at Google Scholar · View at Scopus
  68. A. Awasthi, S. S. Chauhan, and S. K. Goyal, “A multi-criteria decision making approach for location planning for urban distribution centers under uncertainty,” Mathematical and Computer Modelling, vol. 53, no. 1-2, pp. 98–109, 2011. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet · View at Scopus
  69. J. Malczewski and C. Rinner, Multicriteria Decision Analysis in Geographic Information Science, Springer, New York, NY, USA, 2015.
  70. A. Shanian and O. Savadogo, “A methodological concept for material selection of highly sensitive components based on multiple criteria decision analysis,” Expert Systems with Applications, vol. 36, no. 2, pp. 1362–1370, 2009. View at Publisher · View at Google Scholar · View at Scopus
  71. G. Büyüközkan and G. Çifçi, “A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information,” Computers in Industry, vol. 62, no. 2, pp. 164–174, 2011. View at Publisher · View at Google Scholar · View at Scopus
  72. E. Triantaphyllou and A. Sánchez, “A sensitivity analysis approach for some deterministic multi-criteria decision-making methods,” Decision Sciences, vol. 28, no. 1, pp. 151–194, 1997. View at Google Scholar
  73. E. Triantaphyllou, Multi-Criteria Decision Making: A Comparative Study, Kluwer Academic Publishers, Dordrecht, The Netherlands, 2000.
  74. M. Bevilacqua and M. Braglia, “The analytic hierarchy process applied to maintenance strategy selection,” Reliability Engineering and System Safety, vol. 70, no. 1, pp. 71–83, 2000. View at Publisher · View at Google Scholar · View at Scopus
  75. C.-W. Chang, C.-R. Wu, C.-T. Lin, and H.-C. Chen, “An application of AHP and sensitivity analysis for selecting the best slicing machine,” Computers & Industrial Engineering, vol. 52, no. 2, pp. 296–307, 2007. View at Publisher · View at Google Scholar · View at Scopus
  76. D. Choudhary and R. Shankar, “An STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: a case study from India,” Energy, vol. 42, no. 1, pp. 510–521, 2012. View at Publisher · View at Google Scholar · View at Scopus
  77. A. Awasthi, S. S. Chauhan, H. Omrani, and A. Panahi, “A hybrid approach based on SERVQUAL and fuzzy TOPSIS for evaluating transportation service quality,” Computers & Industrial Engineering, vol. 61, no. 3, pp. 637–646, 2011. View at Publisher · View at Google Scholar · View at Scopus
  78. A. Awasthi, S. S. Chauhan, and H. Omrani, “Application of fuzzy TOPSIS in evaluating sustainable transportation systems,” Expert Systems with Applications, vol. 38, no. 10, pp. 12270–12280, 2011. View at Publisher · View at Google Scholar · View at Scopus
  79. A. Awasthi and S. S. Chauhan, “A hybrid approach integrating Affinity Diagram, AHP and fuzzy TOPSIS for sustainable city logistics planning,” Applied Mathematical Modelling, vol. 36, no. 2, pp. 573–584, 2012. View at Publisher · View at Google Scholar · View at Scopus
  80. M. Saisana, A. Saltelli, and S. Tarantola, “Uncertainty and sensitivity analysis techniques as tools for the quality assessment of composite indicators,” Journal of the Royal Statistical Society Series A: Statistics in Society, vol. 168, no. 2, pp. 307–323, 2005. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  81. D. Ben-Arieh, “Sensitivity of multi-criteria decision making to linguistic quantifiers and aggregation means,” Computers and Industrial Engineering, vol. 48, no. 2, pp. 289–309, 2005. View at Publisher · View at Google Scholar · View at Scopus
  82. G. Büyüközkan and G. Çifçi, “A combined fuzzy AHP and fuzzy TOPSIS based strategic analysis of electronic service quality in healthcare industry,” Expert Systems with Applications, vol. 39, no. 3, pp. 2341–2354, 2012. View at Publisher · View at Google Scholar · View at Scopus
  83. M. Zarghami, “Soft computing of the Borda count by fuzzy linguistic quantifiers,” Applied Soft Computing Journal, vol. 11, no. 1, pp. 1067–1073, 2011. View at Publisher · View at Google Scholar · View at Scopus
  84. M. Zarghami and F. Szidarovszky, “On the relation between compromise programming and ordered weighted averaging operator,” Information Sciences, vol. 180, no. 11, pp. 2239–2248, 2010. View at Publisher · View at Google Scholar · View at Scopus
  85. E. R. Vaidogas, E. K. Zavadskas, and Z. Turskis, “Reliability measures in multicriteria decision making as applied to engineering projects,” International Journal of Management and Decision Making, vol. 8, no. 5-6, pp. 497–518, 2007. View at Publisher · View at Google Scholar · View at Scopus
  86. B. J. Garrick, Quantifying and Controlling Catastrophic Risks, Elsevier, Amsterdam, The Netherlands, 2008.
  87. L. F. Gay and S. K. Sinha, “Resilience of civil infrastructure systems: literature review for improved asset management,” International Journal of Critical Infrastructures, vol. 9, no. 4, pp. 330–350, 2013. View at Publisher · View at Google Scholar · View at Scopus
  88. B. J. Jennings, E. D. Vugrin, and D. K. Belasich, “Resilience certification for commercial buildings: a study of stakeholder perspectives,” Environment Systems and Decisions, vol. 33, no. 2, pp. 184–194, 2013. View at Publisher · View at Google Scholar · View at Scopus
  89. G. Lizarralde, K. Chmutina, L. Bosher, and A. Dainty, “Sustainability and resilience in the built environment: the challenges of establishing a turquoise agenda in the UK,” Sustainable Cities and Society, vol. 15, pp. 96–104, 2015. View at Publisher · View at Google Scholar
  90. M. Rausand, Reliability of Safety-Critical Systems: Theory and Applications, Wiley, Chichester, UK, 2014. View at Publisher · View at Google Scholar
  91. E. R. Vaidogas and E. K. Zavadskas, “Introducing reliability measures into multi-criteria decision making,” International Journal of Management and Decision Making, vol. 8, no. 5-6, pp. 475–496, 2007. View at Publisher · View at Google Scholar · View at Scopus
  92. N. D. Singpurwalla, Reliability and Risk. A Bayesian Perspective, Wiley, Chichester, UK, 2006. View at Publisher · View at Google Scholar · View at MathSciNet
  93. E. R. Vaidogas, “On applying sparse and uncertain information to estimating the probability of failure due to rare abnormal situations,” Information Technology and Control, vol. 38, no. 2, pp. 135–146, 2009. View at Google Scholar
  94. J. C. Helton and W. L. Oberkampf, “Alternative representations of epistemic uncertainty,” Reliability Engineering & System Safety, vol. 85, no. 1–3, pp. 1–10, 2004. View at Publisher · View at Google Scholar · View at Scopus
  95. C. J. Roy and W. L. Oberkampf, “A comprehensive framework for verification, validation, and uncertainty quantification in scientific computing,” Computer Methods in Applied Mechanics and Engineering, vol. 200, no. 25–28, pp. 2131–2144, 2011. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  96. M. C. M. Troffaes, G. Walter, and D. Kelly, “A robust Bayesian approach to modeling epistemic uncertainty in common-cause failure models,” Reliability Engineering and System Safety, vol. 125, no. 1, pp. 13–21, 2014. View at Publisher · View at Google Scholar · View at Scopus
  97. E. K. Zavadskas and E. R. Vaidogas, “Multiattribute selection from alternative designs of infrastructure components for accidental situations,” Computer-Aided Civil and Infrastructure Engineering, vol. 24, no. 5, pp. 346–358, 2009. View at Publisher · View at Google Scholar · View at Scopus
  98. S. Mannan, Ed., Lees's Loss Prevention in the Process Industries, Elsevier, Amsterdam, The Netherlands, 2005.
  99. E. Versluis, M. van Asselt, T. Fox, and A. Hommels, “The EU Seveso regime in practice: from uncertainty blindness to uncertainty tolerance,” Journal of Hazardous Materials, vol. 184, no. 1–3, pp. 627–631, 2010. View at Publisher · View at Google Scholar · View at Scopus
  100. L. T. Ostrom and C. A. Wilhelmsen, Risk Assessment. Tools, Techniques, and Their Applications, Wiley, Hoboken, NJ, USA, 2012.
  101. E. R. Vaidogas and J. Šakėnaitė, “Protecting built property against fire disasters: multi-attribute decision making with respect to fire risk,” International Journal of Strategic Property Management, vol. 14, no. 4, pp. 391–407, 2010. View at Publisher · View at Google Scholar · View at Scopus
  102. J.-L. Zhou, Z.-H. Bai, and Z.-Y. Sun, “A hybrid approach for safety assessment in high-risk hydropower-construction-project work systems,” Safety Science, vol. 64, pp. 163–172, 2014. View at Publisher · View at Google Scholar · View at Scopus
  103. M. D. Catrinu and D. E. Nordgård, “Integrating risk analysis and multi-criteria decision support under uncertainty in electricity distribution system asset management,” Reliability Engineering & System Safety, vol. 96, no. 6, pp. 663–670, 2011. View at Publisher · View at Google Scholar · View at Scopus
  104. A. Nieto-Morote and F. Ruz-Vila, “A fuzzy approach to construction project risk assessment,” International Journal of Project Management, vol. 29, no. 2, pp. 220–231, 2011. View at Publisher · View at Google Scholar · View at Scopus
  105. A. Nieto-Morote and F. Ruz-Vila, “A fuzzy multi-criteria decision-making model for construction contractor prequalification,” Automation in Construction, vol. 25, pp. 8–19, 2012. View at Publisher · View at Google Scholar · View at Scopus
  106. Y. Xiang, C. Liu, K. Zhang, and Q. Wu, “Risk analysis and management of submerged floating tunnel and its application,” Procedia Engineering, vol. 4, pp. 107–116, 2010. View at Publisher · View at Google Scholar
  107. Y.-M. Wang, J. Liu, and T. M. S. Elhag, “An integrated AHP-DEA methodology for bridge risk assessment,” Computers & Industrial Engineering, vol. 54, no. 3, pp. 513–525, 2008. View at Publisher · View at Google Scholar · View at Scopus
  108. M. S. El-Abbasy, T. Zayed, M. Ahmed, H. Alzraiee, and M. Abouhamad, “Contractor selection model for highway projects using integrated simulation and analytic network process,” Journal of Construction Engineering and Management, vol. 139, no. 7, pp. 755–767, 2013. View at Publisher · View at Google Scholar · View at Scopus
  109. L. Hui, W. Yongqing, S. Shimei, and S. Baotie, “Study on safety assessment of fire hazard for the construction site,” Procedia Engineering, vol. 43, pp. 369–373, 2012. View at Google Scholar
  110. M. A. Alqassim and N. N. Daeid, “Fires and related incidents in Dubai, United Arab Emirates (2006–2013),” Case Studies in Fire Safety, vol. 2, pp. 28–36, 2014. View at Publisher · View at Google Scholar
  111. D. J. Rasbash, G. Ramachandran, B. Kandola, J. M. Watts, and M. Law, Evaluation of Fire Safety, John Wiley & Sons, Chichester, UK, 2004. View at Publisher · View at Google Scholar
  112. C. M. Zhao, S. M. Lo, J. A. Lu, and Z. Fang, “A simulation approach for ranking of fire safety attributes of existing buildings,” Fire Safety Journal, vol. 39, no. 7, pp. 557–579, 2004. View at Publisher · View at Google Scholar · View at Scopus
  113. J. Wong, H. Li, and J. Lai, “Evaluating the system intelligence of the intelligent building systems—part 1: development of key intelligent indicators and conceptual analytical framework,” Automation in Construction, vol. 17, no. 3, pp. 284–302, 2008. View at Publisher · View at Google Scholar · View at Scopus
  114. J. Wong, H. Li, and J. Lai, “Evaluating the system intelligence of the intelligent building systems. Part 2: construction and validation of analytical models,” Automation in Construction, vol. 17, no. 3, pp. 303–321, 2008. View at Publisher · View at Google Scholar · View at Scopus
  115. E. R. Vaidogas and J. Šakėnaitė, “Multi-attribute decision-making in economics of fire protection,” Engineering Economics, vol. 22, no. 3, pp. 262–270, 2011. View at Google Scholar · View at Scopus
  116. E. R. Vaidogas and L. Linkutė, “Sitting the barrier aimed at protecting roadside property from accidental fires and explosions on road: a pre-optimisation stage,” The Baltic Journal of Road and Bridge Engineering, vol. 7, no. 4, pp. 277–287, 2012. View at Publisher · View at Google Scholar · View at Scopus
  117. E. K. Zavadskas and J. Antucheviciene, “Multiple criteria evaluation of rural building's regeneration alternatives,” Building and Environment, vol. 42, no. 1, pp. 436–451, 2007. View at Publisher · View at Google Scholar · View at Scopus
  118. E. Krygiel and B. Nies, Green BIM: Successful Sustainable Design with Building Information Modeling, Wiley, Indianapolis, Ind, USA, 2008.
  119. AIA, Guide, Instructions and Commentary to the 2013 AIA Digital Practice Documents, The American Institute of Architects, Washington, DC, USA, 2013.
  120. B. A. Wayland, Security for Business Professionals. How to Plan, Implement, and Manage your Company's Security Program, Elsevier, Amsterdam, The Netherlands, 2014.
  121. D. Drengenberg and G. Corley, “Evolution of building code requirements in a post 9/11 world,” CTBUH Journal, no. 3, pp. 32–35, 2011. View at Google Scholar · View at Scopus