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A practical weight sensitivity algorithm for goal and multiple objective programming

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  • Jones, Dylan

Abstract

This paper presents a weight sensitivity algorithm that can be used to investigate a portion of weight space of interest to the decision maker in a goal or multiple objective programme. The preferential information required from the decision maker is an initial estimate of their starting solution, with an equal weights solution being used as a default if this is not available, and preference information that will define the portion of weight space on which the sensitivity analysis is to be conducted. The different types of preferential information and how they are incorporated by the algorithm are discussed. The output of the algorithm is a set of distinct solutions that characterise the portion of weight space searched. The possible different output requirements of decision makers are detailed in the context of the algorithm. The methodology is demonstrated on two examples, one hypothetical and the other relating to predicting cinema-going behaviour. Conclusions and avenues for future research are given.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:213:y:2011:i:1:p:238-245
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    References listed on IDEAS

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    7. P. L. Yu, 1973. "A Class of Solutions for Group Decision Problems," Management Science, INFORMS, vol. 19(8), pages 936-946, April.
    8. 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, January.
    9. X Li & P Beullens & D Jones & M Tamiz, 2009. "An integrated queuing and multi-objective bed allocation model with application to a hospital in China," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(3), pages 330-338, March.
    10. Romero, Carlos, 2001. "Extended lexicographic goal programming: a unifying approach," Omega, Elsevier, vol. 29(1), pages 63-71, February.
    11. 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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    Citations

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    Cited by:

    1. Paola Cappanera & Filippo Visintin & Carlo Banditori, 2018. "Addressing conflicting stakeholders’ priorities in surgical scheduling by goal programming," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 252-271, June.
    2. Dylan F. Jones & Graham Wall, 2016. "An extended goal programming model for site selection in the offshore wind farm sector," Annals of Operations Research, Springer, vol. 245(1), pages 121-135, October.
    3. Amelia Bilbao-Terol & Mariano Jiménez & Mar Arenas-Parra, 2016. "A group decision making model based on goal programming with fuzzy hierarchy: an application to regional forest planning," Annals of Operations Research, Springer, vol. 245(1), pages 137-162, October.
    4. Chang, Ching-Ter, 2011. "Multi-choice goal programming with utility functions," European Journal of Operational Research, Elsevier, vol. 215(2), pages 439-445, December.
    5. Oliveira, Washington A. & Fiorotto, Diego J. & Song, Xiang & Jones, Dylan F., 2021. "An extended goal programming model for the multiobjective integrated lot-sizing and cutting stock problem," European Journal of Operational Research, Elsevier, vol. 295(3), pages 996-1007.
    6. Jones, Dylan & Florentino, Helenice & Cantane, Daniela & Oliveira, Rogerio, 2016. "An extended goal programming methodology for analysis of a network encompassing multiple objectives and stakeholders," European Journal of Operational Research, Elsevier, vol. 255(3), pages 845-855.
    7. Demirci, Mehmet & Bettinger, Pete, 2015. "Using mixed integer multi-objective goal programming for stand tending block designation: A case study from Turkey," Forest Policy and Economics, Elsevier, vol. 55(C), pages 28-36.
    8. Amelia Bilbao-Terol & Mar Arenas-Parra & Verónica Cañal-Fernández & Mariano Jiménez, 2016. "A sequential goal programming model with fuzzy hierarchies to sustainable and responsible portfolio selection problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(10), pages 1259-1273, October.
    9. Jones, Dylan & Labib, Ashraf & Willis, Kevin & Costello, Joseph T & Ouelhadj, Djamila & Ikonen, Emmi Susanna & Dominguez Cainzos, Mikel, 2023. "Multi-criteria mapping and prioritization of Arctic and North Atlantic maritime safety and security needs," European Journal of Operational Research, Elsevier, vol. 307(2), pages 827-841.
    10. Jones, Dylan & Firouzy, Sina & Labib, Ashraf & Argyriou, Athanasios V., 2022. "Multiple criteria model for allocating new medical robotic devices to treatment centres," European Journal of Operational Research, Elsevier, vol. 297(2), pages 652-664.
    11. 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.
    12. Khorramshahgol, Reza & Al-Husain, Raed, 2021. "A GP-AHP approach to Design Responsive Supply Chains for Pareto Customers," Operations Research Perspectives, Elsevier, vol. 8(C).
    13. Jones, D.F. & Treloar, R. & Ouelhadj, D. & Glampedakis, A. & Bartmeyer, P., 2024. "Incorporation of poverty principles into goal programming," Omega, Elsevier, vol. 127(C).
    14. Chandra Ade Irawan & Peter S. Hofman & Hing Kai Chan & Antony Paulraj, 2022. "A stochastic programming model for an energy planning problem: formulation, solution method and application," Annals of Operations Research, Springer, vol. 311(2), pages 695-730, April.
    15. 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.
    16. Kanellopoulos, A. & Gerdessen, J.C. & Claassen, G.D.H., 2015. "Compromise programming: Non-interactive calibration of utility-based metrics," European Journal of Operational Research, Elsevier, vol. 244(2), pages 519-524.
    17. Penn, M.L. & Potts, C.N. & Harper, P.R., 2017. "Multiple criteria mixed-integer programming for incorporating multiple factors into the development of master operating theatre timetables," European Journal of Operational Research, Elsevier, vol. 262(1), pages 194-206.
    18. 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.
    19. Akbari, Negar & Jones, Dylan & Arabikhan, Farzad, 2021. "Goal programming models with interval coefficients for the sustainable selection of marine renewable energy projects in the UK," European Journal of Operational Research, Elsevier, vol. 293(2), pages 748-760.
    20. Mila Bravo & Dylan Jones & David Pla-Santamaria & Francisco Salas-Molina, 2022. "Encompassing statistically unquantifiable randomness in goal programming: an application to portfolio selection," Operational Research, Springer, vol. 22(5), pages 5685-5706, November.
    21. 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.

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