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A methodology for rating and ranking hazards in maritime formal safety assessment using fuzzy logic

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Formal safety assessment of ships has attracted great attention over the last few years. This paper, following a brief review of the current status of marine safety assessment is focused on the hazards identification (HAZID) and prioritisation process. A multicriteria decision making framework, which is based on experts‟ estimation, is then proposed for hazards evaluation. Additionally in this paper many aspects of the evaluation framework are presented including the synthesis of evaluation teams, the assessment of the importance of criteria, the evaluation of the consequences of the alternative hazards and the final ranking of the hazards. The proposed methodology has the innovative feature of embodying techniques of fuzzy logic theory into the classical multicriteria decision analysis. The paper concludes by exploring the potentiality of the above methodology in providing a robust and flexible evaluation framework suitable to the characteristics of a hazard evaluation problem.
Rocznik
Tom
Strony
59--65
Opis fizyczny
Bibliogr. 24 poz., tab.
Twórcy
  • University of the Aegean, Dept. of Shipping Trade and Transport, Chios, Greece
  • University of the Aegean, Dept. of Shipping Trade and Transport, Chios, Greece
  • University of the Aegean, Dept. of Shipping Trade and Transport, Chios, Greece
Bibliografia
  • [1] Baas, S. & Kwakernaak, H. (1977). Rating and ranking of multiple-aspect alternatives using fuzzy sets. Automatica 13, 47-58.
  • [2] Bellman, R. & Zadel, L. (1970). Decision-making in a fuzzy environment. Management Science 17, 4, 141-164.
  • [3] Chen, C. (1998). A study of fuzzy group decision-making method. In 1998 6th National Conference on Fuzzy Sets and Its Applications, vol. 142, pp.174-186.
  • [4] Cheng, C. & Lin, Y. (2002). Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation. European Journal of Operational Research 142, 174-186.
  • [5] Dong, W., Shah, H. & Wong, F. (1985). Fuzzy computations in risk and decision analysis. Civil Engineering Systems 2 , 201-208.
  • [6] Dubois, D. & Prade, H. (1978). Operations on fuzzy numbers. Int. J. Syst. Sci.9, 3, 613-626.
  • [7] Dubois, D. & Prade, H. (1980). Fuzzy Sets and Systems: Theory and Applications. Vol.144 of Mathematics in Science and Engineering. Academic Press Inc., U.S.
  • [8] Gendall, P. (1998). A framework for questionnaire design: Labaw revisited. Marketing Bulletin 9, 28-39.
  • [9] Hague, P. (1993). Questionnaire Design. Kogan Page, London, England.
  • [10] Labaw, P. J. (1980). Advanced Questionnaire Design. Abt Books, Cambridge, MA.
  • [11] Liang, G. S. & Wang, M. J. (1991). A fuzzy multi-criteria decision making method for facility site selection. International Journal of Production Research, 29 (11): 2313-2330.
  • [12] MSA. (1993). Formal Safety Assessment MSC66/14. Submitted by the United Kingdom to IMO Maritime Safety Committee.
  • [13] Nikitakos, G., Dounias, N. & Thomaidis, N. S. (2002). D3.1: Evaluation guidelines. Technical report, contributing to work package III European R&D Results-Assessment and Evaluation of DIAS.net project (project no. IST-2001-35077).
  • [14] Prabhu, T. S. & Vizayakumar, K. (1996). Fuzzy hierarchical decision making (FHDM): A methodology for technology choice. International Journal of Computer Applications in Technology, 9(5): 322-329.
  • [15] Ribeiro, R. (1996). Fuzzy multiple attribute decision making: A review and new preference elicitation techniques. Fuzzy Sets and Systems 78, 155-181.
  • [16] Student Researcher: Online Survey Solutions. Questionnaire Design. Educational Website. http://www.studentresearcher.com.
  • [17] Sudman, S. & Bradburn, N. M. (1983). Asking Questions: Α Practical Guide to Questionnaire Design. Jossey-Bass, San Francisco, CA.
  • [18] THESIS Version 2.02 (1998). The Health, Environment and Safety Information System, User Guide, EQE International, July.
  • [19] Trbojevic, V. M. & Carr, B. J. (2000). Risk based methodology for safety improvements in ports. Journal of Hazardous Materials 71, 467-480.
  • [20] Tseng, T. Y. & Klein, C. (1992). A new algorithm for fuzzy multicriteria decision making. International Journal of Approximating Reasoning 6, 45-66.
  • [21] Wang, J. (2001). The current status and future aspects in Formal Ship Safety Assessment. Safety Science 38, 19-30.
  • [22] Zadeh. L. A. (1965). Fuzzy Sets. Information and Control 8, 338-353.
  • [23] Zadeh, L. (1973). Outline of a new approach to the analysis of complex systems and decision processes. IEEE Trans. Syst. Man Cybern. SMC-3, 1, 28-44.
  • [24] Zimmermann, H. J. (1987). Fuzzy Sets, Decision Making and Expert Systems. International Series in Management Science/ Operations Research. Kluwer Academic, Dordrecht.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-5086b886-5251-402e-93ab-de3d537d63c0
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