This paper analyzes the resolution complexity of a random CSP model named model RBmix, the instance of which is composed by constraints with different length. For model RBmix, the existence of phase transitions has be...This paper analyzes the resolution complexity of a random CSP model named model RBmix, the instance of which is composed by constraints with different length. For model RBmix, the existence of phase transitions has been established and the threshold points have been located exactly. By encoding the random instances into CNF formulas, it is proved that almost all instances of model RBmix have no tree-like resolution proofs of less than exponential size. Thus the model RBmix can generate abundant hard instances in the threshold. This result is of great significance for algorithm testing and complexity analysis in NP-complete problems.展开更多
文摘This paper analyzes the resolution complexity of a random CSP model named model RBmix, the instance of which is composed by constraints with different length. For model RBmix, the existence of phase transitions has been established and the threshold points have been located exactly. By encoding the random instances into CNF formulas, it is proved that almost all instances of model RBmix have no tree-like resolution proofs of less than exponential size. Thus the model RBmix can generate abundant hard instances in the threshold. This result is of great significance for algorithm testing and complexity analysis in NP-complete problems.
