Skip to main content

Part of the book series: Ettore Majorana International Science Series ((EMISS,volume 43))

Abstract

Minimax problems are a very important class of nonsmooth optimization problems. They occur in curve fitting, engineering design, optimal control and many other situations (see [26]) for some specific examples). They are also among the best understood nonsmooth optimization problems, particularly when they involve maxima of smooth functions. There is now a considerable literature dealing with minimax problems and we present a selected list of publications in our references section (see [2], [4], [6], [7], [8], [9], [11], [12], [18], [20], [21], [22], [23], [24], [25], [26], [28], [29], [31], [32]). Looking over these papers, the reader will find that several approaches to minimax algorithms are possible, some of which yield first order methods, while others yield superlinearly converging ones. In this chapter we examine a particularly simple approach to the construction of minimax algorithms, which yields first order methods only.

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 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. L. Armijo. “Minimization of functions having continuous partial derivatives”. Pacific J. Math., 16 (1966), pp. 1–3.

    Article  MathSciNet  MATH  Google Scholar 

  2. T. Baker. “Algorithms for optimal control of systems described by partial and ordinary differential equations”. Ph.D. Thesis, University of California, Berkeley (1988).

    Google Scholar 

  3. R.O. Barr. “An efficient computational procedure for a generalized quadratic programming problem”. SIAM J. Control, 7, No. 3 (1969).

    Google Scholar 

  4. C. Berge. “Topological spaces”. Macmillan, New York, N.Y. ( 1963 ). WileyInterscience, New York, N.Y. (1983).

    Google Scholar 

  5. C. Charalambous and A.R. Conn. “An efficient method to solve the minimax problem directly”. SIAM J. Numerical Analysis, 15 (1978), pp. 162–187.

    Article  MathSciNet  ADS  MATH  Google Scholar 

  6. F.H. Clarke. “Optimization and nonsmooth analysis”. Wiley-Interscience, New York (1983).

    MATH  Google Scholar 

  7. J.M. Danskin. “The theory of minimax with applications”. SIAM J. Appl. Math., 14 (1966), pp. 641–655.

    Article  MathSciNet  MATH  Google Scholar 

  8. V.A. Daugavet and V.N. Malozemov. “Quadratic rate of convergence of a linearization method for solving discrete minimax problems”. U.S.S.R. Comput. Maths. Math. Phys., 21, No. 4 (1981), pp. 19–28.

    Article  MathSciNet  MATH  Google Scholar 

  9. R. Fletcher. “A model algorithm for composite nondifferentiable optimization problems”. Mathematical Programming Studies, 17 (1982), pp. 67–76.

    Article  MathSciNet  MATH  Google Scholar 

  10. M. Frank and P. Wolfe. “An algorithm for quadratic programming”. Naval Research Logistics Quarterly, 3 (1956), pp. 95–110.

    Article  MathSciNet  Google Scholar 

  11. C. Gonzaga, E. Lopak and R. Trahan. “An improved algorithm for optimization problems with functional inequality constraints”. IEEE Trans. on Automatic Control, AC-25, No. 1 (1979), pp. 49–54.

    Google Scholar 

  12. J. Hald and K. Madsen. “Combined LP and quasi-Newton methods for minimax optimization” Mathematical Programming, 20 (1981), pp. 49–62.

    Article  MathSciNet  MATH  Google Scholar 

  13. J.E. Higgins and E. Polak. “Minimizing pseudo-convex functions on convex compact sets”. University of California, Berkeley, Electronics Research Laboratory Memo No. UCB/ERL M88/22. To appear in Jou. Optimization Th..Appl. on 1988.

    Google Scholar 

  14. B. von Hohenbalken. “Simplicial decomposition in nonlinear programming algorithms”. Mathematical Programming, 13 (1977), pp. 49–68.

    Article  MathSciNet  MATH  Google Scholar 

  15. P. Huard. “Programmation mathematic convex”. Rev. Fr. Inform. Rech. Operation, 7 (1968), pp. 43–59.

    MathSciNet  Google Scholar 

  16. P.E. Gill, S.J. Hammarling, W. Murray, M.A. Saunders and M.H. Wright. “User’s guide for LSSOL (version 1.0): a fortran package for constrained linear least-squares and convex quadratic programming”. Technical report SOL 86–1, Department of Operations Research, Stanford University, Stanford (1986).

    Google Scholar 

  17. E.G. Gilbert. “An iterative procedure for computing the minimum of a quadratic forn on a convex set”. SIAM J. Control, 4, No. 1 (1966).

    Google Scholar 

  18. K.C. Kiwiel. “Methods of descent for nondifferentiable optimization”. Springer-Verlag, Berlin-Heidelberg-New York-Tokyo (1985).

    MATH  Google Scholar 

  19. D.G. Kuenberger.“Introduction to linear and nonlinear programming’, Addison-Wesley, New York (1983).

    Google Scholar 

  20. K. Madsen and H. Schjaer-Jacobsen. “Linearly constrained minimax optimization;;. Mathematical Programming, 14 (1978), pp. 208–223.

    Article  MathSciNet  MATH  Google Scholar 

  21. D.Q. Mayne and E. Polak. “An exact penalty function algorithm for optimal control problems with control and terminal inequality constraints, Part 1”. Jou. Optimization Th. Appl., 32, No. 2 (1980), pp. 211–246.

    Article  MathSciNet  MATH  Google Scholar 

  22. D.Q. Mayne and E. Polak. “An exact penalty function algorithm for optimal problems with control and terminal inequality constraints, Part 2”. Jou. Optimization Th. Appl., 32, No. 2 (1980), pp. 345–363.

    Article  MATH  Google Scholar 

  23. W. Murray and M.L. Overton. “A projected Lagrangian algorithm for nonlinear minimax optimization”. SIAM J. Sci. Stat. Cumput., 1, No. 3 (1980).

    Google Scholar 

  24. O. Pironneau and E. Polak. “On the rate of convergence of certain methods of centers”. Mathematica Programming, 2, No. 1 (1972), pp. 230–258.

    Article  MathSciNet  MATH  Google Scholar 

  25. O. Pironneau and E. Polak. “A dual method for optimal control problems with initial and final boundary constraints”. SIAM J. Control, 11, No. 3 (1973), pp. 534–349.

    Article  MathSciNet  MATH  Google Scholar 

  26. E. Polak. “On the mathematical foundations of nondifferentiable optimization in engineering design”. SIAM Review (1987), pp. 21–91.

    Google Scholar 

  27. E. Polak. “Computational methods in optimization: A unified approach”. Academic Press (1971).

    Google Scholar 

  28. E. Polak and J.W. Wiest. “Variable metric techniques for the solution of affimely parametrized nondifferentiable optimal design problems”. University of California, Berkeley, Electronics Research Laboratory Memo No. UCB/ERL M88 /42 (1988).

    Google Scholar 

  29. E. Polak, D.Q, Mayne and J. Higgins. “A superlinearly convergent algorithm for min-max problems”. Proc. 1988 IEEE Conf. on Dec. and Control (1988)

    Google Scholar 

  30. E. Polak, R. Trahan and D.Q. Mayne. “Combined rhase I- rhase II methods of feasible directions”. Mathematical Programming No. 1 (1979), pp. 32–61

    MathSciNet  Google Scholar 

  31. B.N. Pshenichnyi and Yu M. Danilin. “Numerical methods in extremal problems”. Nauka, Moscow (1975).

    Google Scholar 

  32. R.S. Womersley and R. Fletcher. “An algorithm for composite nonsmooth optimization problems”. Jou. Optimization Th. Appl., 48, No. 3 (1986).

    Google Scholar 

  33. P. Wolfe. “Finding the nearest point in a polytope”. Mathematical Programming, 11 (1976), pp. 128–149.

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1989 Springer Science+Business Media New York

About this chapter

Cite this chapter

Polak, E. (1989). Basics of Minimax Algorithms. In: Clarke, F.H., Dem’yanov, V.F., Giannessi, F. (eds) Nonsmooth Optimization and Related Topics. Ettore Majorana International Science Series, vol 43. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-6019-4_20

Download citation

  • DOI: https://doi.org/10.1007/978-1-4757-6019-4_20

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4757-6021-7

  • Online ISBN: 978-1-4757-6019-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics