Fibonacci search
In computer science, the Fibonacci search technique is a method of searching a sorted array using a divide and conquer algorithm that narrows down possible locations with the aid of Fibonacci numbers. Compared to binary search where the sorted array is divided into two arrays which are both examined recursively and recombined, Fibonacci search only examines locations whose addresses have lower dispersion. Therefore, when the elements being searched have non-uniform access memory storage (i.e., the time needed to access a storage location varies depending on the location accessed), the Fibonacci search has an advantage over binary search in slightly reducing the average time needed to access a storage location. Note, that large arrays not fitting in CPU cache or even in RAM can also be considered as non-uniform access examples. Fibonacci search has a complexity of O(log(n)) (see Big O notation).
Fibonacci search was first devised by Jack Kiefer (1953) as a minimax search for the maximum (minimum) of a unimodal function in an interval.
Let k be defined as an element in F, the array of Fibonacci numbers. n = Fm is the array size. If n is not a Fibonacci number, let Fm be the smallest number in F that is greater than n.
The array of Fibonacci numbers is defined where Fk+2 = Fk+1 + Fk, when k ≥ 0, F1 = 1, and F0 = 0.
To test whether an item is in the list of ordered numbers, follow these steps:
Alternative implementation (from "Sorting and Searching" by Knuth):
Given a table of records R1, R2, ..., RN whose keys are in increasing order K1 < K2 < ... < KN, the algorithm searches for a given argument K. Assume N+1 = Fk+1
Step 1. [Initialize] i ← Fk, p ← Fk-1, q ← Fk-2 (throughout the algorithm, p and q will be consecutive Fibonacci numbers)
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