Partition Minimization Technique release_axx243fzwfcqrodqd43pvctpzm

by Arghya Ranjan Das

Released as a post by Research Square Platform LLC.

2022  

Abstract

<jats:title>Abstract</jats:title> There are various algorithms to find the minima of a function, most of them are based on calculating the gradients and using them to find and approximate minima. In this work we will look at a numerical algorithm to find the minimum value of a function, since it is a numerical algorithm hence it does not requires calculation of any gradients. Also the error in the solution decreases exponentially fast with each iteration, thus a highly accurate result can be generated within a small number of iterations. In this algorithm we successively partition the search domain to reduce its size with each iterations and ultimately giving the minimum value within some error limits. Though the algorithm presented here is to find an minima in a given search domain, but with proper parameters it can be used to find the global minima in the search domain.
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