Nelder-Mead 方法是一种直接搜索优化方法，对于随机问题效果尚可。它基于在单纯形的顶点处评估函数，然后迭代地缩小单纯形，直到找到更好的点并达到所需的界限 (Nelder 和 Mead 1965)。Nelder-Mead 方法的实现方式如下NMinimize[f, vars,Method -> "NelderMead"].
Nelder-Mead 方法
另请参阅
随机优化使用 Wolfram|Alpha 探索
参考文献
Lagarias, J. C.; Reeds, J. A.; Wright, M. H.; and Wright, P. E. "Convergence Properties of the Nelder-Mead Algorithm in Low Dimensions." AT&T Bell Laboratories Tech. Rep. Murray Hill, NJ, 1995.Nelder, J. A. and Mead, R. "A Simplex Method for Function Minimization." Comput. J. 7, 308-313, 1965.Press, W. H.; Flannery, B. P.; Teukolsky, S. A.; and Vetterling, W. T. Numerical Recipes in FORTRAN: The Art of Scientific Computing, 2nd ed. Cambridge, England: Cambridge University Press, 1989.Walters, F. H.; Parker, L. R. Jr.; Morgan, S. L.; and Deming, S. N. Sequential Simplex Optimization: A Technique for Improving Quality and Productivity in Research, Development, and Manufacturing. Boca Raton, FL: CRC Press, 1991.Woods, D. J. An Interactive Approach for Solving Multi-Objective Optimization Problems. Ph.D. thesis. Houston, TX: Rice University, 1985.Wright, M. H. "The Nelder-Mead Method: Numerical Experimentation and Algorithmic Improvements." AT&T Bell Laboratories Techn. Rep. Murray Hill, NJ.Wright, M. H. "Direct Search Methods: Once Scorned, Now Respectable." In Numerical Analysis 1995. Papers from the Sixteenth Dundee Biennial Conference held at the University of Dundee, Dundee, June 27-30, 1995 (Ed. D. F. Griffiths and G. A. Watson). London: Longman, Harlow, pp. 191-208, 1996.在 Wolfram|Alpha 中被引用
Nelder-Mead 方法请引用为
Weisstein, Eric W. "Nelder-Mead 方法。" 来自 MathWorld——Wolfram Web 资源。 https://mathworld.net.cn/Nelder-MeadMethod.html