
[1] J.A. Nelder and R. Mead, A simplex method for function minimization, Computer Journal vol. 7 (1965), 308315.

[2] R. Hooke and T. A. Jeeves, Direct Search Solution of Numerical and Statistical Problems, Journal of the ACM, Vol. 8, April 1961, pp. 212229

[3] M. J. D. Powell. The NEWUOA software for unconstrained optimization with derivatives. DAMTP Report 2004/NA05, University of Cambridge, 2004.

[4] Frank Vanden Berghen, Hugues Bersini, CONDOR, a new parallel, constrained extension of Powell’s UOBYQA algorithm: Experimental results and comparison with the DFO algorithm,
Journal of Computational and Applied Mathematics, Elsevier, Volume 181, Issue 1, September 2005, Pages 157175

[5] Intel Math Kernel Library Reference Manual. Optimization Solver Routines: www.intel.com/software/products/mkl/docs/WebHelp/osr/osr_Intro.html

[6] Stefen Boyd, Stanford Engineering Open Courseware, Convex Optimization  see.stanford.edu/see/lecturelist.aspx?coll=2db7ced439d14fdb90e8364129597c87

Backtraking Line Search, ArmijoGoldstein condition (ee364a lecture 15, 18min)

Gradient Descent method (ee364a lecture 15, 24 min)

Steepest Descent method (ee364a lecture 15, 32.1 min)

[7] Anita H.M, Numerical Methods for Scientists and Engineers MacGrawHill, 1991, ISBN 0074600133

Newton, QausiNewton, BFG, BFGS (p366)

Direction Set Methods (p370)

Conjugate Gradient method (p376)

[8] Bjoerck A., Dahlquist G.Numerical mathematics and scientific computation (web draft, 1999) Vols.2,3.

Steepest Descent (p403, §11.2.2)

Newton (p401, §11.2.3)

QuasiNewton Methods (p406, §11.2.3)

[9] S.D.Conte, Carl de Boor Elementary Numerical Analysis  An Algorithmic Approach MacGrawHill 1980 3rdEd

[10] W.H., Teukolsky S.A., Vetterling W.T., Flannery B.P. Numerical Recipes  The Art of Scientific Computing
3nd ed, Cambridge University Press 2007(1988), ISBN13 9780511335556, ISBN13 9780521880688

Simplex Method (p502 §10.5)

Direction Set (Powell’s) method (p509 §10.7)

QuasiNewton (BFGS) (p521 §10.9)

[11] Quarteroni A., Sacco R., Saleri F. Numerical mathematics, 2nd ed., Springer 2007

The Hooke and Jeeves Method (p300 §7.2.1)

Descent Methods (good overview, Newton, quasiNewton, Gradient, Conjugate Gradient method) (p306 §7.2.2)

Newton (p313 §7.2.6)

quasiNewton (p313 §7.2.7)

[12] Schwartz R. Biological modeling and simulation. A survey of practical models, algorithms, and numerical methods MIT2008, ISBN 0262195844

[13] Zarowsky C.J. An introduction to numerical analysis for electrical and computer engineers, Wiley 2004

[14] Wolfram Alpha: Examples: Optimization http://www.wolframalpha.com/examples/Optimization.html ; http://www.wolframalpha.com/input/?i=local+extrema+sin+x^2

[15] 'Mixing C++ an Fortran http://solarianprogrammer.com/2012/05/11/mixedlanguageprogrammingcpp11fortran2008/