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Robustness of weighted goal programming models: an analytical measure and its application to offshore wind-farm site selection in United Kingdom

Author

Listed:
  • Mila Bravo

    (Universitat Politècnica de València (Alcoy Campus))

  • Dylan Jones

    (University of Portsmouth)

  • David Pla-Santamaria

    (Universitat Politècnica de València (Alcoy Campus))

  • Graham Wall

    (University of Portsmouth)

Abstract

This paper proposes a method to measure robustness of weighted goal programming (WGP) models by focusing on random percentage changes in the set of observed technological coefficients that characterize the goal equations. The issue under consideration is to estimate the impact of the random percentage changes on the WGP deviations from the goal targets, the solution to the model before changes being kept equal. Normally distributed and independent percentage changes are assumed. As a result, a measure of robustness is obtained dependent on the parameters of the model, standard deviations of percentage changes, and the solution to the model before changes. A demonstration of the proposed robustness measure on an offshore wind-farm site location model from the literature is developed. The results indicate that robustness of proposed solution to the energy project is high. Conclusions are drawn as to the practicality and usage of the proposed model in comparison to other methodologies for handling uncertainty within the goal programming model.

Suggested Citation

  • Mila Bravo & Dylan Jones & David Pla-Santamaria & Graham Wall, 2018. "Robustness of weighted goal programming models: an analytical measure and its application to offshore wind-farm site selection in United Kingdom," Annals of Operations Research, Springer, vol. 267(1), pages 65-79, August.
    • Handle: RePEc:spr:annopr:v:267:y:2018:i:1:d:10.1007_s10479-017-2437-z
    DOI: 10.1007/s10479-017-2437-z
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    References listed on IDEAS

    as
    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. Dylan Jones & Mehrdad Tamiz, 2010. "Practical Goal Programming," International Series in Operations Research and Management Science, Springer, edition 1, number 978-1-4419-5771-9, July-Dece.
    3. 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.
    4. Aouni, Belaid & Colapinto, Cinzia & La Torre, Davide, 2014. "Financial portfolio management through the goal programming model: Current state-of-the-art," European Journal of Operational Research, Elsevier, vol. 234(2), pages 536-545.
    5. M. A. Yaghoobi & D. F. Jones & M. Tamiz, 2008. "Weighted Additive Models For Solving Fuzzy Goal Programming Problems," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 25(05), pages 715-733.
    6. John Geanakoplos, 2005. "Three brief proofs of Arrow’s Impossibility Theorem," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 26(1), pages 211-215, July.
    7. Thomas L. Saaty & Luis G. Vargas, 2012. "Models, Methods, Concepts & Applications of the Analytic Hierarchy Process," International Series in Operations Research and Management Science, Springer, edition 2, number 978-1-4614-3597-6, July-Dece.
    8. Jones, Dylan & Jimenez, Mariano, 2013. "Incorporating additional meta-objectives into the extended lexicographic goal programming framework," European Journal of Operational Research, Elsevier, vol. 227(2), pages 343-349.
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    Cited by:

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    2. Pandora Gkeka-Serpetsidaki & Georgia Skiniti & Stavroula Tournaki & Theocharis Tsoutsos, 2024. "A Review of the Sustainable Siting of Offshore Wind Farms," Sustainability, MDPI, vol. 16(14), pages 1-29, July.

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