scholarly journals A Polynomial Time Algorithm for 3SAT

2021 ◽  
Vol 13 (3) ◽  
pp. 1-13
Author(s):  
Lizhi Du

By creating new concepts and methods—the checking tree, long unit path, direct contradiction unit pair, indirect contradiction unit pair, additional contradiction unit pair, two-unit layer and three-unit layer—we successfully transform solving a 3SAT problem to solving 2SAT problems in polynomial time. Each time, we add only one layer of the three-unit layers to the two-unit layers to calculate 2SAT paths, respectively. The key is as follows: in each 2SAT path, any two units cannot be a direct contradiction unit pair and cannot be an indirect contradiction unit pair and additional contradiction unit pair. This guarantees that all of the 2SAT paths we got, respectively, can shape at least one long path without contradictions. Thus, we proved that NP = P.

10.29007/v68w ◽  
2018 ◽  
Author(s):  
Ying Zhu ◽  
Mirek Truszczynski

We study the problem of learning the importance of preferences in preference profiles in two important cases: when individual preferences are aggregated by the ranked Pareto rule, and when they are aggregated by positional scoring rules. For the ranked Pareto rule, we provide a polynomial-time algorithm that finds a ranking of preferences such that the ranked profile correctly decides all the examples, whenever such a ranking exists. We also show that the problem to learn a ranking maximizing the number of correctly decided examples (also under the ranked Pareto rule) is NP-hard. We obtain similar results for the case of weighted profiles when positional scoring rules are used for aggregation.


2002 ◽  
Vol 50 (8) ◽  
pp. 1935-1941 ◽  
Author(s):  
Dongning Li ◽  
Yong Ching Lim ◽  
Yong Lian ◽  
Jianjian Song

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