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Monte Carlo Simulation Techniques in a Decision Support System for Group Decision Making

Author

Listed:
  • Antonio Jiménez

    (Madrid Technical University)

  • Alfonso Mateos

    (Madrid Technical University)

  • Sixto Ríos-Insua

    (Madrid Technical University)

Abstract

This paper describes a group decision support system based on an additive multi-attribute utility model for identifying a consensus strategy in group decision-making problems where several decision-makers or groups of decision-makers elicit their own preferences separately. On the one hand, the system provides procedures to quantify the DM’s or group of DMs’ preferences separately. This involves assessing the DM’s or group of DMs’ component utilities that represent their preferences regarding the respective possible attribute values and objective weights that represent the relative importance of the criteria. On the other hand, we propose Monte Carlo simulation techniques for identifying a consensus strategy. An iterative process will be carried out, where, after the simulations have been performed, the imprecise component utilities and weights corresponding to the different DMs or groups of DMs are tightened to output more meaningful information in the next simulations to achieve a consensus strategy. Finally, an application to the evaluation of remedial strategies for restoring contaminated aquatic ecosystems illustrates the usefulness and flexibility of this decision support tool.

Suggested Citation

  • Antonio Jiménez & Alfonso Mateos & Sixto Ríos-Insua, 2005. "Monte Carlo Simulation Techniques in a Decision Support System for Group Decision Making," Group Decision and Negotiation, Springer, vol. 14(2), pages 109-130, March.
    • Handle: RePEc:spr:grdene:v:14:y:2005:i:2:d:10.1007_s10726-005-2406-9
    DOI: 10.1007/s10726-005-2406-9
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    References listed on IDEAS

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    1. Jarke, Matthias & Jelassi, M. Tawfik & Shakun, Melvin F., 1987. ": Towards a negotiation support system," European Journal of Operational Research, Elsevier, vol. 31(3), pages 314-334, September.
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    Cited by:

    1. Jessop, Alan, 2014. "IMP: A decision aid for multiattribute evaluation using imprecise weight estimates," Omega, Elsevier, vol. 49(C), pages 18-29.
    2. Antonio Jiménez-Martín & Eduardo Gallego & Alfonso Mateos & Juan A. Fernández Pozo, 2017. "Restoring a Radionuclide Contaminated Aquatic Ecosystem: A Group Decision Making Problem with Incomplete Information within MAUT Accounting for Veto," Group Decision and Negotiation, Springer, vol. 26(4), pages 653-675, July.
    3. McKenna, R. & Bertsch, V. & Mainzer, K. & Fichtner, W., 2018. "Combining local preferences with multi-criteria decision analysis and linear optimization to develop feasible energy concepts in small communities," European Journal of Operational Research, Elsevier, vol. 268(3), pages 1092-1110.
    4. Wulf, David & Bertsch, Valentin, 2016. "A natural language generation approach to support understanding and traceability of multi-dimensional preferential sensitivity analysis in multi-criteria decision making," MPRA Paper 75025, University Library of Munich, Germany.
    5. Alfonso Mateos & Antonio Jiménez-Martín & Sixto Ríos-Insua, 2015. "A Group Decision-Making Methodology with Incomplete Individual Beliefs Applied to e-Democracy," Group Decision and Negotiation, Springer, vol. 24(4), pages 633-653, July.
    6. Baležentis, Tomas & Streimikiene, Dalia, 2017. "Multi-criteria ranking of energy generation scenarios with Monte Carlo simulation," Applied Energy, Elsevier, vol. 185(P1), pages 862-871.

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