The average complexity of depth-first search with backtracking and cutoff
IBM Journal of Research and Development
Efficient search techniques—an empirical study of the N-Queens problem
IBM Journal of Research and Development
A polynomial time algorithm for the N-Queens problem
ACM SIGART Bulletin
Parallel algorithms and architectures for very fast AI search
Parallel algorithms and architectures for very fast AI search
Performance measurement and analysis of certain search algorithms.
Performance measurement and analysis of certain search algorithms.
Efficient local search for very large-scale satisfiability problems
ACM SIGART Bulletin
Trace-Based Methods for Solving Nonlinear Global Optimization and Satisfiability Problems
Journal of Global Optimization
A Discrete Lagrangian-Based Global-SearchMethod for Solving Satisfiability Problems
Journal of Global Optimization
Two Dogmas of Computationalism
Minds and Machines
Efficient Local Search with Conflict Minimization: A Case Study of the n-Queens Problem
IEEE Transactions on Knowledge and Data Engineering
Local Search for DAG Scheduling and Task Assignment
ICPP '97 Proceedings of the international Conference on Parallel Processing
An efficient non-probabilistic search algorithm for the N-queens problem
ACST'07 Proceedings of the third conference on IASTED International Conference: Advances in Computer Science and Technology
On the density of solutions in equilibrium points for the queens problem
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
The breakout method for escaping from local minima
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Combining local search and backtracking techniques for constraint satisfaction
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
New decision rules for exact search in N-Queens
Journal of Global Optimization
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The n - queens problem is a classical combinatorial search problem. In this paper we give a linear time algorithm for this problem. The algorithm is an extension of one of our previous local search algorithms [3, 4, 6]. On an IBM RS 6000 computer, this algorithm is capable of solving problems with 3,000,000 queens in approximately 55 seconds.