Biased random satisfiability problems: From easy to hard instances

Biased random satisfiability problems: from easy to hard instances.

In this paper we study biased random K -satisfiability ( K -SAT) problems in which each logical variable is negated with probability p . This generalization provides us a crossover from easy to hard problems and would help us in a better understanding of the typical complexity of random K -SAT problems. The exact solution of 1-SAT case is given. The critical point of K -SAT problems and results...

Random constraint satisfaction: Easy generation of hard (satisfiable) instances

In this paper, we try to further demonstrate that the models of random CSP instances proposed by Xu and Li are of theoretical and practical interest. Indeed, these models, called RB and RD, present several nice features. First, it is quite easy to generate random instances of any arity since no particular structure has to be integrated, or property enforced, in such instances. Then, the existen...

Distinguishing Easy and Hard Instances

Hard Instances of Hard Problems

This paper investigates the instance complexities of problems that are hard or weakly hard for exponential time under polynomial time many one reductions It is shown that almost every instance of almost every problem in exponential time has essentially maximal instance complexity It follows that every weakly hard problem has a dense set of such maximally hard instances This extends the theorem ...

Finding Hard Instances of the Satisfiability Problem

Finding sets of hard instances of propositional satissability is of interest for understanding the complexity of SAT, and for experimentally evaluating SAT algorithms. In discussing this we consider the performance of the most popular SAT algorithms on random problems, the theory of average case complexity, the threshold phenomenon, known lower bounds for certain classes of algorithms, and the ...