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Expanding the flexibility of goal programming via preference modelling techniques

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  • Jones, D. F.
  • Tamiz, M.

Abstract

The standard goal programming model only allows linear continuous preference functions to be modelled. In this paper methods for formulating other possible preference structures, such as discontinuities and varying penalty levels dependent on the distance from the goals are proposed. Techniques for ensuring minimal model growth and ease of solution are discussed. An example to illustrate these methods is given.

Suggested Citation

  • Jones, D. F. & Tamiz, M., 1995. "Expanding the flexibility of goal programming via preference modelling techniques," Omega, Elsevier, vol. 23(1), pages 41-48, February.
    • Handle: RePEc:eee:jomega:v:23:y:1995:i:1:p:41-48
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    1. Crarnes, A. & Cooper, W. W. & Harrald, J. & Karwan, K. R. & Wallace, W. A., 1976. "A goal interval programming model for resource allocation in a marine environmental protection program," Journal of Environmental Economics and Management, Elsevier, vol. 3(4), pages 347-362, December.
    2. Charnes, A. & Collomb, B., 1972. "Optimal economic stabilization policy: Linear goal-interval programming models," Socio-Economic Planning Sciences, Elsevier, vol. 6(4), pages 431-435, August.
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    Cited by:

    1. Chang, Ching-Ter, 2011. "Multi-choice goal programming with utility functions," European Journal of Operational Research, Elsevier, vol. 215(2), pages 439-445, December.
    2. Hocine, Amin & Kouaissah, Noureddine & Lozza, Sergio Ortobelli & Aouam, Tarik, 2024. "Modelling De novo programming within Simon’s satisficing theory: Methods and application in designing an optimal offshore wind farm location system," European Journal of Operational Research, Elsevier, vol. 315(1), pages 289-306.
    3. Cherif, Mohamed Sadok & Chabchoub, Habib & Aouni, Belaid, 2008. "Quality control system design through the goal programming model and the satisfaction functions," European Journal of Operational Research, Elsevier, vol. 186(3), pages 1084-1098, May.
    4. Chang, Ching-Ter & Lin, Teng-Chiao, 2009. "Interval goal programming for S-shaped penalty function," European Journal of Operational Research, Elsevier, vol. 199(1), pages 9-20, November.
    5. Romero, Carlos, 2004. "A general structure of achievement function for a goal programming model," European Journal of Operational Research, Elsevier, vol. 153(3), pages 675-686, March.
    6. Aznar, Jeronimo & Guijarro, Francisco, 2007. "Estimating regression parameters with imprecise input data in an appraisal context," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1896-1907, February.
    7. J P Oddoye & M A Yaghoobi & M Tamiz & D F Jones & P Schmidt, 2007. "A multi-objective model to determine efficient resource levels in a medical assessment unit," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(12), pages 1563-1573, December.
    8. Bertomeu, M. & Romero, C., 2001. "Managing forest biodiversity: a zero-one goal programming approach," Agricultural Systems, Elsevier, vol. 68(3), pages 197-213, June.
    9. Jones, Dylan, 2011. "A practical weight sensitivity algorithm for goal and multiple objective programming," European Journal of Operational Research, Elsevier, vol. 213(1), pages 238-245, August.
    10. Hamalainen, Raimo P. & Mantysaari, Juha, 2002. "Dynamic multi-objective heating optimization," European Journal of Operational Research, Elsevier, vol. 142(1), pages 1-15, October.
    11. Tamiz, M. & Mirrazavi, S. K. & Jones, D. F., 1999. "Extensions of Pareto efficiency analysis to integer goal programming," Omega, Elsevier, vol. 27(2), pages 179-188, April.
    12. Kalu, Timothy Ch. U., 1999. "An algorithm for systems welfare interactive goal programming modelling," European Journal of Operational Research, Elsevier, vol. 116(3), pages 508-529, August.
    13. Tom Rihm & Philipp Baumann, 2018. "Staff assignment with lexicographically ordered acceptance levels," Journal of Scheduling, Springer, vol. 21(2), pages 167-189, April.
    14. van Calker, K.J. & Berentsen, P.B.M. & Giesen, G.W.J. & Huirne, R.B.M., 2008. "Maximising sustainability of Dutch dairy farming systems for different stakeholders: A modelling approach," Ecological Economics, Elsevier, vol. 65(2), pages 407-419, April.
    15. Ching-Ter Chang, 2006. "Mixed binary interval goal programming," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(4), pages 469-473, April.
    16. M. Ortuño & B. Vitoriano, 2011. "A goal programming approach for farm planning with resources dimensionality," Annals of Operations Research, Springer, vol. 190(1), pages 181-199, October.
    17. Jiménez, Mariano & Bilbao-Terol, Amelia & Arenas-Parra, Mar, 2021. "Incorporating preferential weights as a benchmark into a Sequential Reference Point Method," European Journal of Operational Research, Elsevier, vol. 291(2), pages 575-585.
    18. Yaghoobi, M.A. & Tamiz, M., 2007. "A method for solving fuzzy goal programming problems based on MINMAX approach," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1580-1590, March.
    19. J Aznar & F Guijarro, 2007. "Modelling aesthetic variables in the valuation of paintings: an interval goal programming approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(7), pages 957-963, July.
    20. Tamiz, Mehrdad & Jones, Dylan & Romero, Carlos, 1998. "Goal programming for decision making: An overview of the current state-of-the-art," European Journal of Operational Research, Elsevier, vol. 111(3), pages 569-581, December.
    21. Chang, Ching-Ter, 2007. "Multi-choice goal programming," Omega, Elsevier, vol. 35(4), pages 389-396, August.
    22. Jones, D.F. & Collins, A. & Hand, C., 2007. "A classification model based on goal programming with non-standard preference functions with application to the prediction of cinema-going behaviour," European Journal of Operational Research, Elsevier, vol. 177(1), pages 515-524, February.

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