Fuzzy Multiple Attributive Group Decision-Making for Conflict Resolution in Collaborative Design

Most conflicts in collaborative design are categorized as the problem of fuzzy multiple attributive group decision-making (FMAGDM). Both fuzzy assessments and the aggregation of multiple experts' opinions should be considered in the conflict resolution process. This paper presents a new approach for the problem, where cooperation degree (CD) and reliability degree (RD) are introduced for aggregating the vague experts' opinions. Furthermore, a fuzzy multiple attributive group decision-making expert system (FMAGDMES) is proposed to provide an interactive way to solve conflicts in collaborative environment. It is an intelligent integrated system because it combines fuzzy set theory with the method of group opinion aggregation. The vehicle performance evaluation as a real case is used to validate the efficiency of the proposed expert system, which is implemented by using c++.

[1]  James J. Buckley,et al.  A fuzzy expert system , 1986 .

[2]  Ching-Lai Hwang,et al.  Multiple Attribute Decision Making: Methods and Applications - A State-of-the-Art Survey , 1981, Lecture Notes in Economics and Mathematical Systems.

[3]  E. Ertugrul Karsak A TWO-PHASE ROBOT SELECTION PROCEDURE , 1998 .

[4]  Chung-Hsing Yeh,et al.  Decision support for bus operations under uncertainty: a fuzzy expert system approach , 1998 .

[5]  J. Grzymala-Busse Managing uncertainty in expert systems , 1991 .

[6]  Sang M. Lee,et al.  An expert system for multiobjective decision making: application of fuzzy linguistic preferences and goal programming , 2002, Fuzzy Sets Syst..

[7]  Shyi-Ming Chen,et al.  A new method for tool steel materials selection under fuzzy environment , 1997, Fuzzy Sets Syst..

[8]  Hans R. Depold,et al.  The Application of Expert Systems and Neural Networks to Gas Turbine Prognostics and Diagnostics , 1998 .

[9]  Ying-Ming Wang,et al.  Multiple attribute decision making based on fuzzy preference information on alternatives: Ranking and weighting , 2005, Fuzzy Sets Syst..

[10]  Pierre Louis Kunsch,et al.  A decision supported system based on the combination of fuzzy expert estimates to assess the financial risks in high-level radioactive waste projects , 2005 .

[11]  Chian-Son Yu,et al.  A GP-AHP method for solving group decision-making fuzzy AHP problems , 2002, Comput. Oper. Res..

[12]  Ian Graham,et al.  Expert Systems: Knowledge, Uncertainty and Decision , 1988 .

[13]  A. I. Ölçer,et al.  A new fuzzy multiple attributive group decision making methodology and its application to propulsion/manoeuvring system selection problem , 2005, Eur. J. Oper. Res..

[14]  Chung-Hsing Yeh,et al.  Fuzzy multicriteria analysis for performance evaluation of bus companies , 2000, Eur. J. Oper. Res..

[15]  Shaw Voon Wong,et al.  A fuzzy logic based expert system for machinability data-on-demand on the Internet , 2002 .

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

[17]  Shyi-Ming Chen A NEW METHOD FOR HANDLING MULTICRITERIA FUZZY DECISION-MAKING PROBLEMS , 1994 .

[18]  Mao-Jiun J. Wang,et al.  A fuzzy multi-criteria decision-making method for facility site selection , 1991 .

[19]  Hans R. Depold,et al.  The Application of Expert Systems and Neural Networks to Gas Turbine Prognostics and Diagnostics , 1998 .

[20]  Ling Zeng Expected Value Method for Fuzzy Multiple Attribute Decision Making , 2006 .

[21]  Maria Meler-Kapcia,et al.  CBR methodology application in an expert system for aided design ship's engine room automation , 2005, Expert Syst. Appl..

[22]  William W. L. Cheung,et al.  A Fuzzy Logic Expert System to Estimate Intrinsic Extinction Vulnerabilities of Marine Fishes to Fishing , 2004 .

[23]  Mao-Jiun J. Wang,et al.  A fuzzy multi-criteria decision-making approach for robot selection , 1993 .