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Interactive Decision Maps, with an Example Illustrating Ocean Waste Management Decisions

  • A. Lotov
  • O. Chernykh
  • V. Bushenkov
  • Hannele Wallenius
  • Jyrki Wallenius
Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 465)

Abstract

Interactive Decision Maps are introduced and illustrated with an ocean waste disposal example, requiring difficult pollution-cost tradeoffs. Interactive Decision Maps are a tool for quickly displaying various decision maps for three or more decision-relevant criteria. They are based on the Generalized Reachable Sets (GRS) approach developed in Russia. Animation of decision maps is also possible. Integration of Interactive Decision Maps with Pareto Race, a free search Multiple Objective Linear Programming procedure, is proposed.

Keywords

Multiple Objective Linear Programming Nondominated Set Ocean Waste Management 

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References

  1. Bushenkov V., Chernykh O., Kamenev G., and Lotov A. (1995), Multi-Dimensional Images Given by Mappings: Construction and Visualization, Pattern Recognition and Image Analysis 5(1), 35–56.Google Scholar
  2. Chernykh O. L. and Kamenev G. K. (1993), Linear Algorithm for a Series of Parallel Two-Dimensional Slices of Multi-Dimensional Convex Polytope, Pattern Recognition and Image Analysis 3(2), 77.Google Scholar
  3. Cohon J.(1978), Multiobjective Programming and Planning, Academic Press, N.Y.Google Scholar
  4. Haimes Y., Tarvainen K., Shima T., and Thadathil J. (1990), Hierarchical Multiobjective Analysis of Large-Scale Systems, Hemisphere Publishing, N.Y.Google Scholar
  5. Korhonen P., and Wallenius J. (1988), A Pareto Race, Naval Research Logistics Quarterly 35, 615–623.Google Scholar
  6. Leschine T., Wallenius H., and Verdini W. (1992), Interactive Multiobjective Analysis and Assimilative Capacity-Based Ocean Disposal Decisions, European Journal of Operational Research 56, 278–289.CrossRefGoogle Scholar
  7. Lieberman E. (1991), Multi-Objective Programming in the USSR, Academic Press, N.Y.Google Scholar
  8. Lotov A. V. (1973), An Approach to Perspective Planning in the Case of Absence of Unique Objective, inProc. of Conf on Systems Approach and Perspective Planning (Moscow, May 1972), Computing Center of the USSR Academy of Sciences, Moscow (in Russian).Google Scholar
  9. Lotov A. V. (1984), Introduction into Mathematical Modeling of Economic Systems, Nauka, Moscow (in Russian).Google Scholar
  10. Lotov A. V. (1996), Comment on D. J. White “A Characterization of the Feasible Set of Objective Function Vectors in Linear Multiple Objective Problems”, European Journal of Operational Research 89, 215–220.CrossRefGoogle Scholar
  11. Wallenius H., Leschine T. M., and Verdini W. (1987), Multiple Criteria Decision Methods in Formulating Marine Pollution Policy: A Comparative Investigation, Research Paper No. 126, Proceedings of the University of Vaasa, Finland.Google Scholar
  12. Wierzbicki A. (1981), A Mathematical Basis for Satisficing Decision Making, in J. Morse (Ed.): Organizations: Multiple Agents with Multiple Criteria, Springer, 465–485.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • A. Lotov
    • 1
  • O. Chernykh
    • 1
  • V. Bushenkov
    • 1
  • Hannele Wallenius
    • 2
  • Jyrki Wallenius
    • 3
  1. 1.Russian Academy of SciencesComputing CenterMoscow B-333Russia
  2. 2.Institute of Industrial ManagementHelsinki University of TechnologyEspooFinland
  3. 3.Helsinki School of EconomicsHelsinkiFinland

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