Ternary search

A ternary search algorithm is a technique in computer science for finding the minimum or maximum of a unimodal function.

The function

Assume we are looking for a maximum of $f(x)$ and that we know the maximum lies somewhere between $A$ and $B$. For the algorithm to be applicable, there must be some value $x$ such that

• for all $a,b$ with $A\leq a<b\leq x$, we have $f(a)<f(b)$, and
• for all $a,b$ with $x\leq a<b\leq B$, we have $f(a)>f(b)$.

Algorithm

Let $f(x)$ be a unimodal function on some interval $[l;r]$. Take any two points $m_{1}$ and $m_{2}$ in this segment: $l<m_{1}<m_{2}<r$. Then there are three possibilities:

• if $f(m_{1})<f(m_{2})$, then the required maximum can not be located on the left side – $[l;m_{1}]$. It means that the maximum further makes sense to look only in the interval $[m_{1};r]$
• if $f(m_{1})>f(m_{2})$, that the situation is similar to the previous, up to symmetry. Now, the required maximum can not be in the right side – $[m_{2};r]$, so go to the segment $[l;m_{2}]$
• if $f(m_{1})=f(m_{2})$, then the search should be conducted in $[m_{1};m_{2}]$, but this case can be attributed to any of the previous two (in order to simplify the code). Sooner or later the length of the segment will be a little less than a predetermined constant, and the process can be stopped.

choice points $m_{1}$ and $m_{2}$:

• $m_{1}=l+(r-l)/3$
• $m_{2}=r-(r-l)/3$

Run time order

$T(n)=T(2n/3)+1=\Theta (\log n)$

Recursive algorithm

def ternary_search(f, left, right, absolute_precision) -> float:
    """Left and right are the current bounds;
    the maximum is between them.
    """
    if abs(right - left) < absolute_precision:
        return (left + right) / 2

    left_third = (2*left + right) / 3
    right_third = (left + 2*right) / 3

    if f(left_third) < f(right_third):
        return ternary_search(f, left_third, right, absolute_precision)
    else:
        return ternary_search(f, left, right_third, absolute_precision)

Iterative algorithm

def ternary_search(f, left, right, absolute_precision) -> float:
    """Find maximum of unimodal function f() within [left, right].
    To find the minimum, reverse the if/else statement or reverse the comparison.
    """
    while abs(right - left) >= absolute_precision:
        left_third = left + (right - left) / 3
        right_third = right - (right - left) / 3

        if f(left_third) < f(right_third):
            left = left_third
        else:
            right = right_third

     # Left and right are the current bounds; the maximum is between them
     return (left + right) / 2

See also

• Newton's method in optimization (can be used to search for where the derivative is zero)
• Golden-section search (similar to ternary search, useful if evaluating f takes most of the time per iteration)
• Binary search algorithm (can be used to search for where the derivative changes in sign)
• Interpolation search
• Exponential search
• Linear search