MCView: An integrated graphical system to support multi-attribute decisions

Abstract The paper presents a DSS for multi-attribute decision problems called MCView. The system combines a process-oriented view of multi-attribute decision making with a comprehensive, graphical user interface. The decision process supported by MCView is based on a two-level representation of evolving preferences, which allows the user to interactively introduce preference information both in the form of holistic choices between alternatives and by directly changing the parameters of a cardinal evaluation method. The graphical user interface of MCView provides comprehensive information about and direct manipulation of all problem components and thus directly supports this learning process.

[1]  Rudolf Vetschera,et al.  A preference-preserving projection technique for MCDM , 1992 .

[2]  R. Vetschera.  Estimating preference cones from discrete choices: Computational techniques and experiences , 1992 .

[3]  J. Siskos.  Assessing a set of additive utility functions for multicriteria decision-making , 1982 .

[4]  Philippe Vincke,et al.  Multicriteria Decision-Aid , 1992 .

[5]  Detlof von Winterfeldt,et al.  Expert systems and behavioral decision research , 1988, Decis. Support Syst..

[6]  Christine T. Kydd,et al.  Cognitive biases in the use of computer-based decision support systems , 1989 .

[7]  Robert Hooke,et al.  `` Direct Search'' Solution of Numerical and Statistical Problems , 1961, JACM.

[8]  G. W. Evans,et al.  An Overview of Techniques for Solving Multiobjective Mathematical Programs , 1984 .

[9]  Elizabeth C. Hirschman,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[10]  Yacov Y. Haimes,et al.  Multiobjective Decision Making: Theory and Methodology , 1983 .

[11]  A. Wierzbicki.  On the completeness and constructiveness of parametric characterizations to vector optimization problems , 1986 .

[12]  Mark Gershon,et al.  The role of weights and scales in the application of multiobjective decision making , 1984 .

[13]  George P. Huber,et al.  METHODS FOR QUANTIFYING SUBJECTIVE PROBABILITIES AND MULTI‐ATTRIBUTE UTILITIES*† , 1974 .

[14]  Bernard Roy,et al.  Problems and methods with multiple objective functions , 1971, Math. Program..

[15]  Herbert Moskowitz,et al.  ASSESSMENT OF MULTIATTRIBUTED MEASURABLE VALUE AND UTILITY FUNCTIONS VIA MATHEMATICAL PROGRAMMING , 1985 .

[16]  J. Brans,et al.  Geometrical representations for MCDA , 1988 .

[17]  Martin Weber.  A Method of Multiattribute Decision Making with Incomplete Information , 1985 .

[18]  Allan D. Shocker,et al.  Estimating the weights for multiple attributes in a composite criterion using pairwise judgments , 1973 .

[19]  Wan Seon Shin,et al.  Interactive multiple objective optimization: Survey I - continuous case , 1991, Comput. Oper. Res..

[20]  Andrzej P. Wierzbicki,et al.  Decision Support Systems Using Reference Point Optimization , 1989 .

[21]  Margaret A. Neale,et al.  Effects of cognitive heuristics and goals on negotiator performance and subsequent goal setting , 1986 .