# Python nelder mead bounds

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I am trying to implement the Nelder-Mead algorithm for optimising a function. The wikipedia page about Nelder-Mead is surprisingly clear about the entire algorithm, except for its stopping criterion. There it sadly says: Check for convergence [clarification needed]. I've gotten comfortable with the Nelder-Mead implementation of the Simplex method, but it does not appear to accept the bounds argument: (...,bounds=[xmin, xmax],...). Reading this documentation it seems only L-BFGS-B, TNC and SLSQP methods accept bounds, and all three of those are based in some way upon Newton's method, and will either ... “Convergence Properties of the Nelder-Mead Simplex Method in Low Dimensions.” SIAM Journal of Optimization. Vol. 9, Number 1, 1998, pp. 112–147. Nelder-Mead function minimization with restarts and verbose. The Nelder-Mead algorithm minimizes functions using only their values, not derivatives. It is slow and steady, relatively insensitive to noise, so often the method to try first. For a clear introduction, read and look at the pictures in Nelder-Mead algorithm. Powell's bound-constrained optimization by quadratic approximation (f77) netlib/opt/subplex f depends on few variables, modification of the Nelder-Mead simplex-search method (no sound theoretical basis), (Matlab version) ## PythonでNelder-Mead法 名前の通り。だが実際は - Qiitaを使ってみたかった - GitHubを使ってみたかった - 他人のコードを見て勉強したかった などの背景があるので結構雑。 - Nelder-... Nelder-Mead Simplex algorithm (method='Nelder-Mead') 是Nelder-Mead法或称下山单纯形法，由Nelder和Mead发现（1965年），这是用于优化多维无约束问题的一种数值方法，属于更一般的搜索算法的类别。