Nelder–Mead method

<p>The Nelder–Mead method (also downhill simplex method, amoeba method, or polytope method) is a <a href="/facts/Numerical_method/MrQIMSIY">numerical method</a> used to find the minimum or maximum of an <a href="/facts/Objective_function/xv5ozuhl">objective function</a> in a multidimensional space. It is a <a href="/facts/Pattern_search_(optimization)/J7HGHb50">direct search</a> method (based on function comparison) and is often applied to nonlinear <a href="/facts/Optimization_(mathematics)/oRn8Iv5I">optimization</a> problems for which derivatives may not be known. However, the Nelder–Mead technique is a <a href="/facts/Heuristic/BcBEkv9c">heuristic</a> search method that can converge to <a href="/facts/Stationary_point/f56GSgBj">non-stationary points</a> on problems that can be solved by alternative methods.
</p><p>The Nelder–Mead technique was proposed by <a href="/facts/John_Nelder/28u4s8J9">John Nelder</a> and <a href="/facts/Roger_Mead/AR7I6jY8">Roger Mead</a> in 1965, as a development of the method of Spendley et al.
</p>

Nelder–Mead method open-in-new

Nelder–Mead method