Exhaustive search

The Exhaustive Search is an exceptionally basic and trivial search routine. It iteratively produces possible solutions to a given problem, checks to see if the problem is solved, and continues until a correct solution is generated, at which point the solution is returned. Variations on this algorithm include returning a set of all solutions (for problems without a unique solution).

The exhaustive search algorithm produces the entire solution space for the problem (typically represented as a tree data structure), and traverses it in either a depth-first or breadth-first fashion. Pruning techniques (such as alpha-beta pruning used in game theory) can be used to reduce the search space. Randomization can be applied to improve runtimes, though there is often little-to-no computational benefit to doing this.

Exhaustive searches are also known as backtracking algorithms, though not all backtracking algorithms are exhaustive. is about trying every possible way to search for a solution. It is usually combined with pruning to reduce the number of items to search for. It is also known as Backtracking.

A generalized pseudocode algorithm for the exhaustive search can be defined thusly: backtrack(int sol, int depth) {  if (issolution(sol)) printsolution(sol) else{ solgenerated = generatesolution backtrack(solgenerated, depth+1) } }

The exhaustive algorithm for sorting an array of integers in ascending order can be defined thusly (in prolog syntax): /* is a the list sorted?*/ isSorted([]). /*an empty list is sorted*/ isSorted([_|[]]). /*a list of one element is sorted*/ isSorted([[First|Second]|Rest]) :- First<=Second, isSorted([second|rest]).

/*is one list a permutation of another?*/ permutation([],[]). permutation([A],[A]). permutation(List1,[List2H|List2T]) :- sameLength(List1,[List2H|List2T]), member(List2H,List1),removed(List1,List2H,Others),permutation(Others,List2T)

/* support functions */ sameLength([],[]). sameLength([_|Tail1],[_|Tail2]) :- sameLength(Tail1,Tail2). removed([Head|Tail],Head,Tail). removed([Head|Tail],X,[Head|Tail2]) :- removed(Tail,X,Tail2).

/* sample call */ ?- isSorted([5,9,6,2,1,3,4,8,7,0],X). /* sort the array and put the result in X */

X = [0,1,2,3,4,5,6,7,8,9]         /* sample output */

This sort produces a permutation of the array, checks to see if it is sorted, and continues until it reaches the first permutation that is sorted, giving the algorithm a running time of O(n!). For comparison, a quicksort has a running time of O(n*log(n)). This exhaustive sort is also an exhaustive search algorithm because every possible solution is produced and examined before a result is returned; a permutation is produced, and if it is incorrect the algorithm backtracks and tries a different permutation

The linear search algorithm is another example of an exhaustive algorithm.