Nelder-Mead Simplex Optimization Routine for Large-Scale Problems: A Distributed Memory Implementation

The Nelder-Mead simplex method is an optimization routine that works well with irregular objective functions. For a function of $n parameters, it compares the objective function at the n+1 vertices of a simplex and updates the worst vertex through simplex search steps. However, a standard serial implementation can be prohibitively expensive for optimizations over a large number of parameters. We describe an implementation of the...