Trajectories in Phase Diagrams, Growth Processes, and Computational Complexity: How Search Algorithms Solve the 3-Satisfiability Problem
- 19 February 2001
- journal article
- Published by American Physical Society (APS) in Physical Review Letters
- Vol. 86 (8) , 1654-1657
- https://doi.org/10.1103/physrevlett.86.1654
Abstract
Decision and optimization problems typically fall into one of two categories for any particular solving algorithm. The problem is either solved quickly (easy) or demands an impractically long computational effort (hard). Here we show that some characteristic parameters of problems can be tracked during a run of the algorithm defining a trajectory through the parameter space. Focusing on 3-satisfiability, a recognized representative of hard problems, we analyze trajectories generated by search algorithms. These trajectories can cross well-defined phases, corresponding to domains of easy or hard instances, and allow one to successfully predict the times of resolution.Keywords
All Related Versions
This publication has 7 references indexed in Scilit:
- Typical Solution Time for a Vertex-Covering Algorithm on Finite-Connectivity Random GraphsPhysical Review Letters, 2001
- Determining computational complexity from characteristic ‘phase transitions’Nature, 1999
- Statistical mechanics of the random-satisfiability modelPhysical Review E, 1997
- Analysis of Two Simple Heuristics on a Random Instance ofk-satJournal of Algorithms, 1996
- Probabilistic analysis of a generalization of the unit-clause literal selection heuristics for the k satisfiability problemInformation Sciences, 1990
- Many hard examples for resolutionJournal of the ACM, 1988
- A Computing Procedure for Quantification TheoryJournal of the ACM, 1960