Multiple Criteria Visual Interactive System with Focused Contouring of Efficient Criterion Vectors

  • Yong Sun Choi
  • Soung Hie Kim
Conference paper


A multiple criteria DSS MC-VISA (Multiple Criteria Visual Interactive System utilizing Approximation) is introduced. MC-VISA is composed of four subsystems: 1) Model manager helps a DM to build, save, retrieve, and edit MOLP models; 2) ASEOV presents the stepwise focused structure of efficient criterion vectors and generates candidate goals for new search directions; 3) VIM displays the efficient trajectories along the search direction and acquires the DM’s preference; and 4) Mediator interfaces the three components and guides a DM through the decision making process. Menus and interactive uses of computer graphics allow a DM much flexibility over problem solving with MC-VISA. MC-VISA is designed in Turbo-Pascal on a personal computer. An illustrative problem solving with MC-VISA is provided.


Search Direction Initial Contour Polyhedral Cone Criterion Vector Goal Selection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Choi, Y. S. and Kim, S. H. (1993), “An improved multiple criteria visual interactive method with stepwise focused contouring of efficient criterion vectors”, Computers and Operations Research, forthcoming.Google Scholar
  2. Kim, S. H. and Gal, T. (1992), “A new interactive algorithm for multicriteria linear programming using maximally changeable dominance cone”, European Journal of Operational Research 64 (1), 126–137.CrossRefGoogle Scholar
  3. Korhonen, P. and Laakso, J. (1986), “A visual interactive method for solving the multiple criteria problem”, European Journal of Operational Research 24, 277–287.MathSciNetMATHCrossRefGoogle Scholar
  4. Korhonen, P. and Wallenius, J. (1988), “A Pareto race”, Naval Research Logistics Quarterly 35 (6), 615–323.MATHCrossRefGoogle Scholar
  5. Nakayama, T., Takeguichi, T., and Sano, M. (1983), “Interactive graphics for portfolio selection”, in: P. Hansen (ed.), Essays and Surveys on Multiple Criteria Decision Making, Springer, New York.Google Scholar
  6. Shin, W. S. and Ravindran, A. (1991), “Interactive multiple objective optimization: Survey I–continuous case”, Computers and Operations Research 18, 97–114.MathSciNetMATHCrossRefGoogle Scholar
  7. Wallenius, J. (1975), “Comparative evaluation of some interactive approaches to multicriterion optimization”, Management Science 21 (12), 1387–1396.Google Scholar
  8. Winkels, H.-M. and Meika, M. (1984), “An Integration of Efficiency Projections into the Geoffrion approach for multiobjective linear programming”, European Journal of Operational Research 16, 113–127.MathSciNetMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag New York, Inc. 1994

Authors and Affiliations

  • Yong Sun Choi
    • 1
  • Soung Hie Kim
    • 2
  1. 1.Dept. of Business AdministrationINJE UniversityKimhaeKorea
  2. 2.Dept. of Management Information SystemsKAISTSeoulKorea

Personalised recommendations