Advertisement

SMAA in Robustness Analysis

  • Risto LahdelmaEmail author
  • Pekka Salminen
Chapter
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 241)

Abstract

Stochastic multicriteria acceptability analysis (SMAA) is a simulation based method for discrete multicriteria decision aiding problems where information is uncertain, imprecise, or partially missing. In SMAA, different kind of uncertain information is represented by probability distributions. Because SMAA considers simultaneously the uncertainty in all parameters, it is particularly useful for robustness analysis. Depending on the problem setting, SMAA determines all possible rankings or classifications for the alternatives, and quantifies the possible results in terms of probabilities. This chapter describes SMAA in robustness analysis using a real-life decision problem as an example. Basic robustness analysis is demonstrated with respect to uncertainty in criteria and preference measurements. Then the analysis is extended to consider also the structure of the decision model.

References

  1. 1.
    Angilella, S., Corrente, S., Greco, S.: Stochastic multiobjective acceptability analysis for the Choquet integral preference model and the scale construction problem. Eur. J. Oper. Res. 240 (1), 172–182 (2015)CrossRefGoogle Scholar
  2. 2.
    Babalos, V., Philippas, N., Doumpos, M., Zopounidis, C.: Mutual funds performance appraisal using stochastic multicriteria acceptability analysis. Appl. Math. Comput. 218 (9), 5693–5703 (2012)Google Scholar
  3. 3.
    Cohen, S., Doumpos, M., Neofytou, E., Zopounidis, C.: Assessing financial distress where bankruptcy is not an option: an alternative approach for local municipalities. Eur. J. Oper. Res. 218 (1), 270–279 (2012)CrossRefGoogle Scholar
  4. 4.
    Corrente, S., Figueira, J.R., Greco, S.: The SMAA-PROMETHEE method. Eur. J. Oper. Res. 239 (2), 514–522 (2014)CrossRefGoogle Scholar
  5. 5.
    David, H.A., Nagaraja, H.N.: Order statistics. Wiley Online Library (1970)Google Scholar
  6. 6.
    Durbach, I., Lahdelma, R., Salminen, P.: The analytic hierarchy process with stochastic judgements. Eur. J. Oper. Res. 238 (2), 552–559 (2014)CrossRefGoogle Scholar
  7. 7.
    Kontu, K., Rinne, S., Olkkonen, V., Lahdelma, R., Salminen, P.: Multicriteria evaluation of heating choices for a new sustainable residential area. Energy Build. 93, 169–179 (2015)CrossRefGoogle Scholar
  8. 8.
    Lahdelma, R., Salminen, P.: SMAA-2: stochastic multicriteria acceptability analysis for group decision making. Oper. Res. 49 (3), 444–454 (2001)CrossRefGoogle Scholar
  9. 9.
    Lahdelma, R., Salminen, P.: Pseudo-criteria versus linear utility function in stochastic multi-criteria acceptability analysis. Eur. J. Oper. Res. 141 (2), 454–469 (2002)CrossRefGoogle Scholar
  10. 10.
    Lahdelma, R., Salminen, P.: Stochastic multicriteria acceptability analysis using the data envelopment model. Eur. J. Oper. Res. 170 (1), 241–252 (2006)CrossRefGoogle Scholar
  11. 11.
    Lahdelma, R., Salminen, P.: Prospect theory and stochastic multicriteria acceptability analysis (SMAA). Omega 37 (5), 961–971 (2009)CrossRefGoogle Scholar
  12. 12.
    Lahdelma, R., Salminen, P.: A method for ordinal classification in multicriteria decision making. In: Proceedings of the 10th IASTED International Conference on Artificial Intelligence and Applications, vol. 674, pp. 420–425 (2010)Google Scholar
  13. 13.
    Lahdelma, R., Salminen, P.: Stochastic multicriteria acceptability analysis (SMAA). In: Ehrgott, M., Figueira, J., Greco, S. (eds.) Trends in Multiple Criteria Decision Analysis. International Series in Operations Research and Management Science, vol. 142, pp. 285–316. Springer, Berlin (2010)Google Scholar
  14. 14.
    Lahdelma, R., Salminen, P.: The shape of the utility or value function in stochastic multicriteria acceptability analysis. OR Spectr. 34 (4), 785–802 (2012)CrossRefGoogle Scholar
  15. 15.
    Lahdelma, R., Hokkanen, J., Salminen, P.: SMAA-stochastic multiobjective acceptability analysis. Eur. J. Oper. Res. 106 (1), 137–143 (1998)CrossRefGoogle Scholar
  16. 16.
    Lahdelma, R., Miettinen, K., Salminen, P.: Ordinal criteria in stochastic multicriteria acceptability analysis (SMAA). Eur. J. Oper. Res. 147 (1), 117–127 (2003)CrossRefGoogle Scholar
  17. 17.
    Lahdelma, R., Miettinen, K., Salminen, P.: Reference point approach for multiple decision makers. Eur. J. Oper. Res. 164 (3), 785–791 (2005)CrossRefGoogle Scholar
  18. 18.
    Lahdelma, R., Makkonen, S., Salminen, P.: Multivariate Gaussian criteria in SMAA. Eur. J. Oper. Res. 170 (3), 957–970 (2006)CrossRefGoogle Scholar
  19. 19.
    Lahdelma, R., Makkonen, S., Salminen, P.: Two ways to handle dependent uncertainties in multi-criteria decision problems. Omega 37 (1), 79–92 (2009)CrossRefGoogle Scholar
  20. 20.
    Leskinen, P., Viitanen, J., Kangas, A., Kangas, J.: Alternatives to incorporate uncertainty and risk attitude in multicriteria evaluation of forest plans. For. Sci. 52 (3), 304–312 (2006)Google Scholar
  21. 21.
    Menou, A., Benallou, A., Lahdelma, R., Salminen, P.: Decision support for centralizing cargo at a Moroccan airport hub using stochastic multicriteria acceptability analysis. Eur. J. Oper. Res. 204 (3), 621–629 (2010)CrossRefGoogle Scholar
  22. 22.
    Taylor, B.N.: Guidelines for evaluating and expressing the uncertainty of NIST measurement results. Tech. Rep. 1297, National Institute of Standards and Technology (1994)Google Scholar
  23. 23.
    Tervonen, T.: JSMAA: open source software for SMAA computations. Int. J. Syst. Sci. 45 (1), 69–81 (2014)CrossRefGoogle Scholar
  24. 24.
    Tervonen, T., Figueira, J.R.: A survey on stochastic multicriteria acceptability analysis methods. J. Multi-Criteria Decis. Anal. 15 (1–2), 1–14 (2008)CrossRefGoogle Scholar
  25. 25.
    Tervonen, T., Lahdelma, R.: Implementing stochastic multicriteria acceptability analysis. Eur. J. Oper. Res. 178 (2), 500–513 (2007)CrossRefGoogle Scholar
  26. 26.
    Tervonen, T., Figueira, J.R., Lahdelma, R., Dias, J.A., Salminen, P.: A stochastic method for robustness analysis in sorting problems. Eur. J. Oper. Res. 192 (1), 236–242 (2009)CrossRefGoogle Scholar
  27. 27.
    Tervonen, T., van Valkenhoef, G., Baştürk, N., Postmus, D.: Hit-and-run enables efficient weight generation for simulation-based multiple criteria decision analysis. Eur. J. Oper. Res. 224 (3), 552–559 (2013)CrossRefGoogle Scholar
  28. 28.
    Wang, H., Jiao, W., Lahdelma, R., Zhu, C., Zou, P.: Stochastic multicriteria acceptability analysis for evaluation of combined heat and power units. Energies 8 (1), 59–78 (2015)CrossRefGoogle Scholar
  29. 29.
    Yevseyeva, I.: Solving classification problems with multicriteria decision aiding approaches. Ph.D. thesis, Jyväskylä Studies in Computing 84 (2007)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Energy TechnologyAalto UniversityEspooFinland
  2. 2.School of Business and EconomicsUniversity of JyväskyläJyväskyläFinland

Personalised recommendations