IDEAS home Printed from https://ideas.repec.org/a/ags/remaae/12358.html
   My bibliography  Save this article

A Generalised Concept of Dominance in Linear Programming Models

Author

Listed:
  • Drynan, Ross G.

Abstract

The notion of dominance most familiar to agricultural economists is perhaps the decision theoretic concept entailed in comparing one risky prospect to others. But dominance concepts are also relevant in the linear programming context, for example in identifying redundant constraints. In this note, the standard concept of dominance in linear programming is generalized by defining dominance with respect to differing levels of information about the programming problem.

Suggested Citation

  • Drynan, Ross G., 1987. "A Generalised Concept of Dominance in Linear Programming Models," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 55(02), pages 1-7, August.
  • Handle: RePEc:ags:remaae:12358
    DOI: 10.22004/ag.econ.12358
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/12358/files/55020140.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.12358?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Fishburn, Peter C., 1974. "Convex stochastic dominance with continuous distribution functions," Journal of Economic Theory, Elsevier, vol. 7(2), pages 143-158, February.
    2. Gerald L. Thompson & Fred M. Tonge & Stanley Zionts, 1966. "Techniques for Removing Nonbinding Constraints and Extraneous Variables from Linear Programming Problems," Management Science, INFORMS, vol. 12(7), pages 588-608, March.
    3. G. Hanoch & H. Levy, 1969. "The Efficiency Analysis of Choices Involving Risk," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 36(3), pages 335-346.
    4. Vijay S. Bawa, 1982. "Research Bibliography---Stochastic Dominance: A Research Bibliography," Management Science, INFORMS, vol. 28(6), pages 698-712, June.
    5. Drynan, Ross G., 1987. "Allocative vs. Technical Efficiency, and Related Matters in Linear Programming," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 55(02), pages 1-8, August.
    6. Kmietowicz, Z. W. & Pearman, A. D., 1982. "Decision theory and strict ranking of probabilities," European Journal of Operational Research, Elsevier, vol. 9(4), pages 397-404, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Andrey Lizyayev, 2012. "Stochastic dominance efficiency analysis of diversified portfolios: classification, comparison and refinements," Annals of Operations Research, Springer, vol. 196(1), pages 391-410, July.
    2. Ogryczak, Wlodzimierz & Ruszczynski, Andrzej, 1999. "From stochastic dominance to mean-risk models: Semideviations as risk measures," European Journal of Operational Research, Elsevier, vol. 116(1), pages 33-50, July.
    3. Raymond H. Chan & Ephraim Clark & Xu Guo & Wing-Keung Wong, 2020. "New development on the third-order stochastic dominance for risk-averse and risk-seeking investors with application in risk management," Risk Management, Palgrave Macmillan, vol. 22(2), pages 108-132, June.
    4. Chan, Raymond H. & Clark, Ephraim & Wong, Wing-Keung, 2012. "On the Third Order Stochastic Dominance for Risk-Averse and Risk-Seeking Investors," MPRA Paper 42676, University Library of Munich, Germany.
    5. Nowak, Maciej, 2004. "Preference and veto thresholds in multicriteria analysis based on stochastic dominance," European Journal of Operational Research, Elsevier, vol. 158(2), pages 339-350, October.
    6. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections," JRFM, MDPI, vol. 11(1), pages 1-29, March.
    7. W. Wong & R. Chan, 2008. "Prospect and Markowitz stochastic dominance," Annals of Finance, Springer, vol. 4(1), pages 105-129, January.
    8. Jianping Yang & Chaoqun Zhao & Weiru Chen & Diwei Zhou & Shuguang Han, 2022. "Fraction-Degree Reference Dependent Stochastic Dominance," Methodology and Computing in Applied Probability, Springer, vol. 24(2), pages 1193-1219, June.
    9. Chan, Raymond H. & Clark, Ephraim & Wong, Wing-Keung, 2016. "On the Third Order Stochastic Dominance for Risk-Averse and Risk-Seeking Investors with Analysis of their Traditional and Internet Stocks," MPRA Paper 75002, University Library of Munich, Germany.
    10. Chang, C-L. & McAleer, M.J. & Wong, W.-K., 2016. "Management Science, Economics and Finance: A Connection," Econometric Institute Research Papers EI2016-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Andrey Lizyayev, 2010. "Stochastic Dominance Efficiency Analysis of Diversified Portfolios: Classification, Comparison and Refinements," Tinbergen Institute Discussion Papers 10-084/2, Tinbergen Institute.
    12. Peter J. Phillips & Gabriela Pohl, 2017. "Terrorist choice: a stochastic dominance and prospect theory analysis," Defence and Peace Economics, Taylor & Francis Journals, vol. 28(2), pages 150-164, March.
    13. Arvanitis, Stelios & Post, Thierry & Potì, Valerio & Karabati, Selcuk, 2021. "Nonparametric tests for Optimal Predictive Ability," International Journal of Forecasting, Elsevier, vol. 37(2), pages 881-898.
    14. Hardaker, J. Brian & Lien, Gudbrand D., 2003. "Stochastic Efficiency Analysis With Risk Aversion Bounds: A Simplified Approach," Working Papers 12954, University of New England, School of Economics.
    15. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Decision Sciences, Economics, Finance, Business, Computing, and Big Data: Connections," Tinbergen Institute Discussion Papers 18-024/III, Tinbergen Institute.
    16. Martin Branda & Miloš Kopa, 2014. "On relations between DEA-risk models and stochastic dominance efficiency tests," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(1), pages 13-35, March.
    17. Liqun Liu & Jack Meyer, 2021. "Stochastic superiority," Journal of Risk and Uncertainty, Springer, vol. 62(3), pages 225-246, June.
    18. Reid, Donald W. & Tew, Bernard V., 1987. "An Evaluation Of Expected Value And Expected Value-Variance Criteria In Achieving Risk Efficiency In Crop Selection," Northeastern Journal of Agricultural and Resource Economics, Northeastern Agricultural and Resource Economics Association, vol. 16(2), pages 1-9, October.
    19. Post, Thierry & Kopa, Miloš, 2013. "General linear formulations of stochastic dominance criteria," European Journal of Operational Research, Elsevier, vol. 230(2), pages 321-332.
    20. Zentner, Robert P. & Greene, Duty D. & Hickenbotham, Terry L. & Eidman, Vernon R., 1981. "Ordinary And Generalized Stochastic Dominance: A Primer," Staff Papers 14184, University of Minnesota, Department of Applied Economics.

    More about this item

    Keywords

    Research Methods/ Statistical Methods;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:remaae:12358. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaresea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.