Efficient local search with conflict minimization: a case study of the n-queens problem

Backtracking search is frequently applied to solve a constraint-based search problem, but it often suffers from exponential growth of computing time. We present an alternative to backtracking search: local search with conflict minimization. We have applied this general search framework to study a benchmark constraint-based search problem, the n-queens problem. An efficient local search algorithm for the n-queens problem was implemented. This algorithm, running in linear time, does not backtrack. It is capable of finding a solution for extremely large size n-queens problems. For example, on a workstation it can find a solution for 3000000 queens in less than 55 s.