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For unconstrained numerical optimization I have been using the book "Numerical Methods for Unconstrained Optimization and Nonlinear Equations" by Dennis and Schnabel. I found it to be a great book (thanks J.M. for the suggestion) and fared very well with it. Now I'm wondering if there is such an easy (!) to understand book for constrained optimization. It should cover topics like:

  • Inner points methods
  • Penalty methods (exact and multiple)
  • SQP methods (including SQP-Trust-Regions)
  • Active sets strategies

And maybe nonsmooth optimization:

  • Moreau Yosida regularization
  • proximal point method
  • Tikhonov regularization
  • subgradient method

Especially important for me, is a good and easy coverage of the SQP algorithm.

Thank you for your time!

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Looks to be a taller order... :) I'll check my bibliography and report back. –  J. M. Jul 20 '12 at 11:02
    
Any news on this J.M. ? :) –  Chris Aug 17 '12 at 21:29
    
Turns out, it's harder to find "easy" refs for this subject. I'll post something when I find anything. –  J. M. Aug 18 '12 at 2:30

1 Answer 1

One that does some, but not all of what you ask is Bazaraa, Sherali and Shetty (1993) Nonlinear programming theory and applications. 2nd ed. John Wiley and Sons.

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