Skip to main content

From Statistical Decision Theory to Robust Optimization: A Maximin Perspective on Robust Decision-Making

  • Chapter
  • First Online:
Robustness Analysis in Decision Aiding, Optimization, and Analytics

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 241))

Abstract

As attested by the prevalence of worst-case-based robustness analysis in many fields, Wald’s maximin paradigm (circa 1940) plays a central role in the broad area of decision-making under uncertainty. The objective of this chapter is therefore twofold. First, to examine the basic conceptual and modeling aspects of this ostensibly intuitive, yet controversial paradigm, so as to clarify some of the issues involved in its deployment in decision-making in the face of a non-probabilistic uncertainty. Second, to elucidate the differences between this paradigm and other maximin paradigms, such as those used in error analysis and game theory. We thereby chart the journey of this paradigm from the field of statistical decision theory to that of modern robust optimization, highlighting its use in the latter, as a tool for dealing with both local and global robustness. We also look briefly at the relationship between probabilistic and worst-case-based robustness analysis.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Andronov, A.A., Pontriagin, L.S.: Robust systems. Dokl. Akad. Nauk SSSR 14, 247–250 (1937) (in Russian)

    Google Scholar 

  2. Andronov, A.A., Vitt, A.A., Khaikin, S.E.: Theory of Oscillations. Nauka, Moscow (1959) (in Russian)

    Google Scholar 

  3. Barmish, B.R., Lagoa, C.M., Tempo, R.: Radially truncated uniform distributions for probabilistic robustness of control systems. In: Proceedings of the American Control Conference, Albuquerque, pp. 853–857 (1997)

    Google Scholar 

  4. Bell, K.J.: Some observations n the teaching and practices of pessimization. Heat Transfer Eng. 13 (1), 5–6 (1992)

    Article  Google Scholar 

  5. Ben-Tal A., El Ghaoui, L., Nemirovski, A.: Robust Optimization. Princeton University Press, Princeton (2009)

    Book  Google Scholar 

  6. Ben-Tal, A., Golany, B., Shtern, S.: Robust multi-echelon multi-period inventory control. Eur. J. Oper. Res. 199, 922–935 (2009)

    Article  Google Scholar 

  7. Ben-Tal, A., Hazan, E., Koren, T., Mannor, S.: Oracle-based robust-optimization via online learning. Oper. Res. 63 (3), 628–638 (2015)

    Article  Google Scholar 

  8. Bertsimas, D., Brown, D.B., Caramanis, C.: Theory and applications of robust optimization. SIAM Rev. 53 (3), 464–501 (2011)

    Article  Google Scholar 

  9. Box, G.E., Andersen, S.L.: Permutation theory in the derivation of robust criteria and the study of departures from assumption. J. R. Stat. Soc. 17 (1), 1–34 (1955)

    Google Scholar 

  10. Chen, X., Aravena, J.L., Zhou, K.: Risk analysis in robust control—making the case for probabilistic robust control. In: Proceedings of the 2005 American Control Conference, Portland, vol. 3, pp. 1533–1538 (2005)

    Google Scholar 

  11. Chen, X., Zhou, K., Aravena, J.: Probabilistic robustness analysis—risks, complexity, and algorithms. SIAM J. Control. Optim. 47 (5), 2693–2723 (2008)

    Article  Google Scholar 

  12. Corbett, J.O.: Uncertainty in risk analysis: an alternative approach through pessimisation. J. Radiol. Prot. 8 (2), 107–117 (1988)

    Google Scholar 

  13. Donoho, D.L., Johnstone, I.M.: Minimax estimation via wavelet shrinkage. Ann. Stat. 26 (3), 879–921 (1998)

    Article  Google Scholar 

  14. Donoho, D.L., Johnstone, I.M., Kerkyacharian, G., Picard, D.: Wavelet shrinkage: asymptopia? J. R. Stat. Soc. B 57 (2), 301–369 (1995)

    Google Scholar 

  15. Dorato, P., Drenick, R.F.: Optimality, sensitivity, and game theory. In: Radanović, L. (ed.) Sensitivity Methods in Control Theory, pp. 78–102. Pergamon Press, New York (1966)

    Google Scholar 

  16. Elishakoff, I., Ohsaki, M.: Optimization and Anti-optimization of Structures Under Uncertainty. Imperial College Press, London (2010)

    Book  Google Scholar 

  17. Ellsberg, D.: Risk, ambiguity and the Savage axioms. Q. J. Econ. 75 (4), 643–669 (1961)

    Article  Google Scholar 

  18. Gabrel, V., Murat, C., Thiele, A.: Recent advances in robust optimization: an overview. Eur. J. Oper. Res. 235 (3), 471–483 (2014)

    Article  Google Scholar 

  19. Gilboa, I., Schmeidler D.: Maximin expected utility with non-unique prior. J. Math. Econ. 18, 141–153 (1989)

    Article  Google Scholar 

  20. Guerrava-Vázquez, F., Rückmann, J.J.: Semi-infinite programming. In: Cochran, J.J. (ed.) Wiley Encyclopedia of Operations Research and Management Science. Wiley, New York (2010)

    Google Scholar 

  21. Hart, A., Roelofs, W., Crocker, J., Murray, A., Boatman, N., Hugo, S., Fitzpatrick, S., Flari, V.: Quantitative approaches to the risk assessment of GM crops. Defra Research Contract CPEC38. Central Science Laboratory, Sand Hutton (2007)

    Google Scholar 

  22. Hayes, K.R., Barry, S.C., Hosack, G.R., Peters, G.W.: Severe uncertainty and info-gap decision theory. Methods Ecol. Evol. 4, 601–611 (2013)

    Article  Google Scholar 

  23. Hindrichsen, D., Pritchard, A.J.: Stability radii of linear systems. Syst. Control Lett. 7, 1–10 (1986)

    Article  Google Scholar 

  24. IECRC: Chemical reaction engineering. Ind. Eng. Chem. Res. 58 (7), 15–17 (1966)

    Google Scholar 

  25. McKenzie, W.M.C.: Design of Structural Elements to Eurocodes. Palgrave, Basingstoke (2013)

    Google Scholar 

  26. Milne, W.E., Reynolds, R.R.: Fifth-order methods for the numerical solution of ordinary differential equations. J. ACM 9 (1), 64–70 (1962)

    Article  Google Scholar 

  27. Milnor, J.: Games against nature. U.S. Air Force Project Rand, Research Memorandum RM-679 (1951)

    Google Scholar 

  28. Morgenstern, O.: Abraham Wald, 1902–1950. Econometrica 19 (4), 361–367 (1951)

    Article  Google Scholar 

  29. Mulvey, J.M., Vanderbei, R.J., Zenios, S.A.: Robust Optimization of Large-Scale Systems. Oper. Res. 43 (2), 264–281 (1995)

    Article  Google Scholar 

  30. Mutapcic, A., Boyd, S.: Cutting-set methods for robust convex optimization with pessimizing oracles. Optim. Methods Softw. 24 (3), 381–406 (2009)

    Article  Google Scholar 

  31. Oskooi, A., Mutapcic, A., Noda, S., Joannopoulos, J.D., Boyd, S.P., Johnson, S.G.: Robust optimization of adiabatic tapers for coupling to slow-light photonic-crystal waveguides. Opt. Express 20 (19), 21558–21575 (2012)

    Article  Google Scholar 

  32. Owhadi, H., Scovel, C.: Machine Wald (2015). arXiv:1508.02449, http://arxiv.org/abs/1508.02449

  33. Pervozvanski, A.A.: Sensitivity, robustness and efficiency of adaptation. Int. J. Adapt. Control Signal Process. 6, 183–191 (1992)

    Article  Google Scholar 

  34. Rawls, J.: Theory of Justice. Belknap Press, Cambridge (1971)

    Google Scholar 

  35. Rustem, B., Howe, M.: Algorithms for Worst-case Design and Applications to Risk Management. Princeton University Press, Princeton (2002)

    Google Scholar 

  36. Savage, L.J.: The theory of statistical decision. J. Am. Stat. Assoc. 46 (253), 55–67 (1951)

    Article  Google Scholar 

  37. Savage, L.J.: The foundation of statistics revisited. In: Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, University of California Press, Berkeley. 1, 575–586 (1961)

    Google Scholar 

  38. Sheynin, O.B.: Origin of the theory of errors. Nature 211, 1003–1004 (1966)

    Article  Google Scholar 

  39. Sniedovich, M.: A bird’s view of info-gap decision theory. J. Risk Finance 11 (3), 268–283 (2010)

    Article  Google Scholar 

  40. Sniedovich, M.: Black swans, new Nostradamuses, voodoo decision theories and the science of decision-making under severe uncertainty. Int. Trans. Oper. Res. 19 (1–2), 253–281 (2012)

    Article  Google Scholar 

  41. Sniedovich, M.: Fooled by local robustness. Risk Anal. 32 (10), 1630–1637 (2012)

    Google Scholar 

  42. Sniedovich, M.: The elephant in the rhetoric on info-gap decision theory. Ecol. Appl. 24 (1), 229–233 (2014)

    Article  Google Scholar 

  43. Stein, O.: How to solve a semi-infinite optimization problem. Eur. J. Oper. Res. 223, 312–320 (2012)

    Article  Google Scholar 

  44. Tintner, G.: Abraham Wald’s contributions to econometrics. Ann. Math. Stat. 23 (1), 21–28 (1952)

    Article  Google Scholar 

  45. von Neumann, J., Morgenstern, O.: Theory of Games and Economic Behavior. Princeton University Press, Princeton (1944); Quotes from the third edition, 1953; sixth printing, 1955

    Google Scholar 

  46. Wald, A.: Contributions to the theory of statistical estimation and testing hypotheses. Ann. Math. Stat. 10 (4), 299–326 (1939)

    Article  Google Scholar 

  47. Wald, A.: Statistical decision functions which minimize the maximum risk. Ann. Math. 46 (2), 265–280 (1945)

    Article  Google Scholar 

  48. Wald, A.: Statistical Decision Functions. Wiley, New York (1950)

    Google Scholar 

  49. Wasserman, L.: Minimax Theory Saves The World (2012). https://normaldeviate.wordpress.com/2012/07/17/minimax-theory-saves-the-world/

    Google Scholar 

  50. Wilf, H.S.: Maximally stable numerical integration. J. Soc. Ind. Appl. Math. 8 (3), 537–540 (1960)

    Article  Google Scholar 

  51. Zlobec, S.: Survey of input optimization. Optimization 18, 309–348 (1987)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Moshe Sniedovich .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Sniedovich, M. (2016). From Statistical Decision Theory to Robust Optimization: A Maximin Perspective on Robust Decision-Making. In: Doumpos, M., Zopounidis, C., Grigoroudis, E. (eds) Robustness Analysis in Decision Aiding, Optimization, and Analytics. International Series in Operations Research & Management Science, vol 241. Springer, Cham. https://doi.org/10.1007/978-3-319-33121-8_4

Download citation

Publish with us

Policies and ethics