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Interactive Multiple Objective Programming: Concepts, Current Status, and Future Directions

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Readings in Multiple Criteria Decision Aid

Abstract

This paper discusses 32 topics that summarize interactive multiple objective programming, the area represented by STEM by Benayoun, de Montgolfier, Tergny and Larichev (1971), the Geoffrion-Dyer-Feinberg Procedure (1972), the Zionts-Wallenius procedure (1976 and 1983), Wierzbicki’s Reference Point Method (1977, 1982 and 1986), etc. The concensus is that a spectrum of interactive procedures is necessary because the procedure to use on a given application is usually problem and user dependent.

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References

  • Aronson, J.E. (1989), “A survey of dynamic network flows”, Annals of Operations Research, to appear.

    Google Scholar 

  • Benayoun, R., de Montgolfier, J., Tergny, J. and Larichev, O. (1971), “Linear programming with multiple objective functions! step method (STEM)”, Mathematical Programming, Vol. 1, No. 3, 366–375.

    Article  Google Scholar 

  • Brockhoff, K. (1985), “Experimental test of MCDM algorithms in a modular approach”, European Journal of Operat ional Research, Vol. 22, No. 2, 159–166.

    Article  Google Scholar 

  • Chankong, V. and Haimes, Y.Y. (1978), “The interactive surrogate worth trade-off (ISWT) method for multiobjective decision-making”, Lecture Notes in Economics and Mathematical Systems, Vol. 155, Springer-Verlag, 42–67.

    Google Scholar 

  • Chankong, V. and Haimes, Y.Y. (1983), Multiobjective Decision Making: Theory and Methodology, North-Holland, New York.

    Google Scholar 

  • Ecker, J.G., Hegner, N.S. and Kouada, I.A. (1980), “Generating all maximal efficient faces for multiple objective linear programs”, Journal of Optimization Theory and Applications, Vol. 30, No. 3, 353–381.

    Article  Google Scholar 

  • Franz, L.S. and Lee, S.M. (1980), “A goal programming based interactive decision support system”, Lecture Notes in Economics and Mathematical Systems, Vol. 190, Springer- Verlag, 110–115.

    Google Scholar 

  • Gal, T. (1977), “A general method for determining the set of all efficient solutions to a linear vectormaximum problem”, European Journal of Operational Research, Vol. 1, No. 5, 307–322.

    Article  Google Scholar 

  • Gardiner, L.R. (1989), “Unified Interactive Multiple Objective Programming”, Ph.D. Dissertation, Department of Management Science amp; Information Technology, University of Georgia, Athens, Georgia, USA.

    Google Scholar 

  • Gardner, J.C., Huefner, R.J. and Lotfi, V. (1989), “A multi-period audit staff planning model using multiple objectives s development and evaluation”, Decision Sciences, to appear.

    Google Scholar 

  • Geoffrion, A.M., Dyer, J.S. and Feinberg, A. (1972), “An interactive approach for multicriterion optimization, with an application to the operation of an academic department”, Management Science, Vol. 19, No. 4, 357–368.

    Article  Google Scholar 

  • IBM Document No. GH19-1091-1 (1979), “IBM Mathematical Programming System Extended/370: Primer”, IBM Corporation, Data Processing Division, White Plains, New York, USA.

    Google Scholar 

  • Ignizio, J.P. (1982), Linear Programming in Single- amp; Multiple-Objective Systems, Englewood Cliffs, New Jerseys Prentice- Hall.

    Google Scholar 

  • Isermann, H. and Steuer, R.E. (1988), “Computational experience concerning payoff tables and minimum criterion values over the efficient set”, European Journal of Operational Research, Vol. 33, No. 1, 91–97.

    Article  Google Scholar 

  • Isermann, H. and Naujoks, G. (1984), “Operating Manual for the EFFACET Multiple Objective Linear Programming Package”, Fakultät fĂĽr Wirtschaftswissenschaften, Universität Bielefeld West Germany.

    Google Scholar 

  • Isermann, H. (1977), “The enumeration of the set of all efficient solutions for a linear multiple objective program”, Operational Research Quarterly, Vol. 38, No. 3, 711–725.

    Article  Google Scholar 

  • Kennington, J.L. (1980), Algorithms for Network Programming, New Yorks John Wiley amp; Sons, 291 pp.

    Google Scholar 

  • Korhonen, P.J. and Laakso, J. (1986), “A visual interactive method for solving the multiple criteria problem”, European Journal of Operational Research, Vol. 24, No. 2, 277–287.

    Article  Google Scholar 

  • Korhonen. P.J. and Wallenius, J. (1988), “A Pareto Race”, Naval Research Logistics, Vol. 35, No. 6, 615–623.

    Article  Google Scholar 

  • Lasdon, L.S. and Waren, A. D. (1986), “GRG2 User’s Guide”, University of Texas, Austin, Texas, USA.

    Google Scholar 

  • Lee, S.M. and Shim, J.P. (1986), “Interactive goal programming on the microcomputer to establish priorities for small business”, Journal of the Operational Research Society, Vol. 37, No. 6, 571–577.

    Google Scholar 

  • Lewandowski, A., Kreglewski, T., Rogowski, T. and Wierzbicki, A.P., (1987), “Decision support systems of DIDAS family (dynamic interactive decision analysis and support)”, Archiwum Automatyki i Telemechaniki, Vol. 32, No. 4, 221– 246.

    Google Scholar 

  • Lieberman, E.R. (1990), Multi -Objective Programming in the USSR, book manuscript, School of Management, State University of New York at Buffalo, Buffalo, New York, USA.

    Google Scholar 

  • Liou, F. H. (1984), “A routine for Generating Grid Point Defined Weighting Vectors”, Masters Thesis, Department of Management Science amp; Information Technology, University of Georgia, Athens, Georgia, USA.

    Google Scholar 

  • Murtaugh, B.A. and Saunders, M. A. (1987), “MINOS 5.1 User’s Guide”, Report SOL 83–20R, Department of Operations Research, Stanford University, Stanford, California, USA.

    Google Scholar 

  • Nakayama, H. and Furukawa, K. (1985), “Satisficing trade-off method with an application to multiobjective structural design”, Large Scale Systems, Vol. 8, No. 1, 47–57.

    Google Scholar 

  • Nakayama, H. and Sawaragi, Y. (1984), “Satisficing trade-off method for multiobjective programming.” Lecture Notes in Economics and Mathematical Systems, Vol. 229, Springer- Verlag, 113–122.

    Google Scholar 

  • Ramesh, R., Karwan, M.H. and Zionts, S. (1989), “Interactive multicriteria linear programming: an extension of the method of Zionts and Wallenius”, Naval Research Logistics, Vol. 36, No. 3, 321–335.

    Article  Google Scholar 

  • Silverman, J., Steuer, R.E. and Whisman, A.W. (1988), “A multi-period, multiple criteria optimization system for manpower planning”, European Journal of Operational Research, Vol. 34, No. 2, 160–170.

    Article  Google Scholar 

  • Stam, A., Joachimsthaler, E.A. and Gardiner, L.R. (1989), “A Multiobjective Model for Sales Force Sizing and Deployment”, Department of Management Science amp; Information Technology, University of Georgia, Athens, Georgia, USA.

    Google Scholar 

  • Steuer, R.E. (1989), “Operating Manual for the ADBASE Multiple Objective Linear Programming Package”, Department of Management Science amp; Information Technology, University of Georgia, Athens, Georgia, USA.

    Google Scholar 

  • Steuer, R.E. (1986), Multiple Criteria Optimization: Theory, Computation, and Application, ( originally published by John Wiley amp; Sons, New York, now being republished by Krieger Publishing, Melbourne, Florida ), 546 pp.

    Google Scholar 

  • Steuer, R.E. and Choo, E.U. (1983), “An interactive weighted tchebycheff procedure for multiple objective programming”, Mathematical Programming, Vol. 26, No. 1, 326–344.

    Article  Google Scholar 

  • Steuer, R.E. and Wood, E.F. (1986), “On the 0-1 implementation of the tchebycheff solution approacht A water quality illustration”, Large Scale Systems, Vol. 10, No. 3, 243–256.

    Google Scholar 

  • Wierzbicki, A.P. (1977), “Basic properties of scalarizing fune- tionals for multiobjective optimization”, Mathematische Operationsforschung und Statistik — Series Optimization, Vol. 8, No. 1, 55–60.

    Article  Google Scholar 

  • Wierzbicki, A.P. (1982), “A mathematical basis for satisficing decision making”, Mathematical Modelling, Vol. 3, 391–405.

    Article  Google Scholar 

  • Wierzbicki, A.P. (1986), “On the completeness and constructive- ness of parametric characterizations to vector optimization problems”, OR Spektrum, Vol. 8, No. 2, 73–87.

    Article  Google Scholar 

  • 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, Vol. 16, No. 1, 113–127.

    Article  Google Scholar 

  • Yu, P.L. (1974), “Cone convexity, cone extreme points, and non- dominated solutions in decision problems with multi-objectives”, Journal of Optimization Theory and Applications, Vol. 14, No. 3, 319–377.

    Article  Google Scholar 

  • Zeleny, M. (1989), “Stable patterns from decision-producing networks: new interfaces of DSS and MCDM”, MCBM WorldScan, Vol. 3, Nos. 2 & 3, 6–7.

    Google Scholar 

  • Zeleny, M. (1974), “Linear multiobjective programming”, Lecture Notes in Economics and Mathematical Systems, No. 95, Berlins Springer-Verlag.

    Google Scholar 

  • Zionts, S. and Wallenius, J. (1976), “An interactive programming method for solving the multiple criteria problem”, Management Science, Vol. 22, No. 6, 652–663.

    Article  Google Scholar 

  • Zionts, S. and Wallenius, J. (1983), “An interactive multiple objective linear programming method for a class of underlying nonlinear utility functions”, Management Science, Vol. 29, No. 5, 519–529.

    Article  Google Scholar 

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Steuer, R.E., Gardiner, L.R. (1990). Interactive Multiple Objective Programming: Concepts, Current Status, and Future Directions. In: Bana e Costa, C.A. (eds) Readings in Multiple Criteria Decision Aid. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-75935-2_18

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  • DOI: https://doi.org/10.1007/978-3-642-75935-2_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-75937-6

  • Online ISBN: 978-3-642-75935-2

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