  A new 1D search method is proposed for minimizing an arbitrary real valued
function. The algorithm is a modification of the interval halving method which
is based on dividing the interval of uncertainty by three points into four
equal parts. The trichotomy method is based on dividing the interval by five
points into six equal parts and provides the interval reducing exactly three
times in every iteration. New algorithm's performance has been extensively
tested and compared to well-known 1D search algorithms: the interval halving
method, golden section method, Fibonacci search. The results show that the
trichotomy method usually require less calculations of the values of the
minimized function to determine the minimum point with the given accuracy. Also
it has better accuracy when finding the minimum point after using N
calculations of the function values.
