Derivative-Free optimization algorithms. These algorithms do not require gradient information. More importantly, they can be used to solve non-smooth optimization problems.
Changes in version 2018.2-1 (2018-4-01) o Set oshrink=1 to enable "restarting" of Nelder-Mead due to stagnation (thanks to Simon Wessing)
Changes in version 2017.12-1 (2017-12-20) o fixed a bug in the code, which impacts the "restarting" of Nelder-Mead due to stagnation (thanks to Simon Wessing)
Changes in version 2016.7-1 (2011-07-08)
o Used a slightly modified code for hjk() and hjkb()
Changes in version 2011.8-1 (2011-08-12)
o Bounds constrained Hooke-Jeeves hjkb()
Changes in version 2011.7-2 (2011-07-26)
o Bounds constrained Nelder-Mead nmkb().
Changes in version 2011.7-1
o Hooke-Jeeves minimization routine hjk().
Changes in version 2011.5-1
o Fixed minor bug in the re-definition of objective function inside for maximization.
o Nelder-Mead minimization routine nmk().