A Fuzzy Model for Design Evaluation Based on Multiple Criteria Analysis in Engineering Systems

Before implementing a design of a large engineering system different design proposals are evaluated and ranked according to different criteria, such as, safety, cost and technical performance. The experts' knowledge about these criteria is usually vague and/or incomplete, and their nature may be quantitative or qualitative. Therefore the preference modelling for the criteria could imply the use of different types of information such as numerical and/or linguistic (non-homogeneous framework). However, in most of evaluation processes the experts are forced to provide their scores in the same expression domain and in the same scale. The aim of this paper is to propose an evaluation model based on a multi-criteria decision analysis that offers to the experts the possibility of expressing their knowledge in a non-homogeneous evaluation framework, such that the experts can provide their assessments within different domains and scales according to their knowledge and the nature of the criteria. To do so, we propose the use of the fuzzy logic and the fuzzy linguistic approach in order to manage the uncertainty related to the information provided by the experts.

[1]  Gert de Cooman,et al.  A behavioral model for linguistic uncertainty , 2001, Inf. Sci..

[2]  S. Orlovsky Decision-making with a fuzzy preference relation , 1978 .

[3]  Francisco Herrera,et al.  A 2-tuple fuzzy linguistic representation model for computing with words , 2000, IEEE Trans. Fuzzy Syst..

[4]  Herman Akdag,et al.  Linguistic Modifiers in a Symbolic Framework , 2001, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[5]  Jian-Bo Yang,et al.  Fuzzy Rule-Based Evidential Reasoning Approach for Safety Analysis , 2004, Int. J. Gen. Syst..

[6]  Mao-Jiun J. Wang,et al.  A MULTIPLE CRITERIA LINGUISTIC DECISION-MODEL (MCLDM) FOR HUMAN DECISION-MAKING , 1994 .

[7]  J. B. Bowles,et al.  Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis , 1995 .

[8]  Mao-Jiun J. Wang,et al.  Personnel selection using fuzzy MCDM algorithm , 1994 .

[9]  José L. Verdegay,et al.  Linguistic decision‐making models , 1992, Int. J. Intell. Syst..

[10]  Chen T. Chen,et al.  Applying Linguistic Decision-Making Method to Deal with Service Quality Evaluation Problems , 2001, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[11]  Ronald R. Yager,et al.  An approach to ordinal decision making , 1995, Int. J. Approx. Reason..

[12]  Piero P. Bonissone,et al.  Selecting Uncertainty Calculi and Granularity: An Experiment in Trading-off Precision and Complexity , 1985, UAI.

[13]  Francisco Herrera,et al.  A multigranular hierarchical linguistic model for design evaluation based on safety and cost analysis , 2005, Int. J. Intell. Syst..

[14]  Adedeji B. Badiru,et al.  Fuzzy modeling and analytic hierarchy processing to quantify risk levels associated with occupational injuries. I. The development of fuzzy-linguistic risk levels , 1996, IEEE Trans. Fuzzy Syst..

[15]  Francisco Herrera,et al.  The 2-Tuple Linguistic Computational Model. Advantages of Its Linguistic Description, Accuracy and Consistency , 2001, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[16]  Jian-Bo Yang,et al.  Multi-person and multi-attribute design evaluations using evidential reasoning based on subjective safety and cost analyses , 1996 .

[17]  Slawomir Zadrozny,et al.  Computing with Words in Decision Making Through Individual and Collective Linguistic Choice Rules , 2001, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[18]  Francisco Herrera,et al.  An Approach for Combining Linguistic and Numerical Information Based on the 2-Tuple Fuzzy Linguistic Representation Model in Decision-Making , 2000, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[19]  Francisco Herrera,et al.  Managing non-homogeneous information in group decision making , 2005, Eur. J. Oper. Res..

[20]  Ronald R. Yager,et al.  Non-numeric multi-criteria multi-person decision making , 1993 .

[21]  Francisco Herrera,et al.  A Sequential Selection Process in Group Decision Making with a Linguistic Assessment Approach , 1995, Inf. Sci..

[22]  Waldemar Karwowski,et al.  Potential applications of fuzzy sets in industrial safety engineering , 1986 .

[23]  C. Pappis,et al.  A fuzzy-linguistic approach to a multi-criteria sequencing problem , 1996 .

[24]  Marc Roubens,et al.  Fuzzy sets and decision analysis , 1997, Fuzzy Sets Syst..

[25]  Francisco Herrera,et al.  A model based on linguistic 2-tuples for dealing with multigranular hierarchical linguistic contexts in multi-expert decision-making , 2001, IEEE Trans. Syst. Man Cybern. Part B.

[26]  Wei Li,et al.  The limiting distribution of the residual lifetime of a Markov repairable system , 1993 .

[27]  Gloria Bordogna,et al.  An Ordinal Information Retrieval Model , 2001, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[28]  Ching-Hsue Cheng,et al.  Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation , 2002, Eur. J. Oper. Res..