Skip to main content

Minimax Methods

  • Chapter
Book cover Practical Optimization
  • 6868 Accesses

Abstract

In many scientific and engineering applications it is often necessary to minimize the maximum of some quantity with respect to one or more independent variables. Algorithms that can be used to solve problems of this type are said to be minimax algorithms. In the case where the quantity of interest depends on a real-valued parameter w that belongs to a set S, the objective function can be represented by f(x, w) and the solution of the minimax problem pertaining to f(x, w) amounts to finding a vector variable x that minimizes the maximum of f(x, w) over wS. There is also a discrete version of this problem in which the continuous parameter w is sampled to obtain discrete values S = {w i : i = 1, ..., L} ⊂ S and the corresponding minimax optimization problem is to find a vector x that minimizes the maximum of f(x, w i) over w iS d .

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 69.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 89.99
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. C. Charalambous, “A unified review of optimization,” IEEE Trans. Microwave Theory and Techniques, vol. MTT-22, pp. 289–300, Mar. 1974.

    Article  MathSciNet  Google Scholar 

  2. C. Charalambous, “Acceleration of the least-pth algorithm for minimax optimization with engineering applications,” Mathematical Programming, vol. 17, pp. 270–297, 1979.

    Article  MATH  MathSciNet  Google Scholar 

  3. A. Antoniou, “Improved minimax optimisation algorithms and their application in the design of recursive digital filters,” Proc. Inst. Elect. Eng., part G, vol. 138, pp. 724–730, Dec. 1991.

    Google Scholar 

  4. A. Antoniou, Digital Signal Processing: Signals, Systems, and Filters, McGraw-Hill, New York, 2005.

    Google Scholar 

  5. C. Charalambous and A. Antoniou, “Equalisation of recursive digital filters,” Proc. Inst. Elect. Eng., part G, vol. 127, pp. 219–225, Oct. 1980.

    Google Scholar 

  6. C. Charalambous, “Design of 2-dimensional circularly-symmetric digital filters,” Proc. Inst. Elect. Eng., part G, vol. 129, pp. 47–54, Apr. 1982.

    Google Scholar 

Download references

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer Science+Business Media, LLC

About this chapter

Cite this chapter

(2007). Minimax Methods. In: Practical Optimization. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-71107-2_8

Download citation

  • DOI: https://doi.org/10.1007/978-0-387-71107-2_8

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-387-71106-5

  • Online ISBN: 978-0-387-71107-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics