Relevant bibliographies by topics / 3-Satisfiability

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic '3-Satisfiability'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "3-Satisfiability"

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Bazuhair, Muna Mohammed, Siti Zulaikha Mohd Jamaludin, Nur Ezlin Zamri, Mohd Shareduwan Mohd Kasihmuddin, Mohd Asyraf Mansor, Alyaa Alway, and Syed Anayet Karim. "Novel Hopfield Neural Network Model with Election Algorithm for Random 3 Satisfiability." Processes 9, no. 8 (July 26, 2021): 1292. http://dx.doi.org/10.3390/pr9081292.

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One of the influential models in the artificial neural network (ANN) research field for addressing the issue of knowledge in the non-systematic logical rule is Random k Satisfiability. In this context, knowledge structure representation is also the potential application of Random k Satisfiability. Despite many attempts to represent logical rules in a non-systematic structure, previous studies have failed to consider higher-order logical rules. As the amount of information in the logical rule increases, the proposed network is unable to proceed to the retrieval phase, where the behavior of the Random Satisfiability can be observed. This study approaches these issues by proposing higher-order Random k Satisfiability for k ≤ 3 in the Hopfield Neural Network (HNN). In this regard, introducing the 3 Satisfiability logical rule to the existing network increases the synaptic weight dimensions in Lyapunov’s energy function and local field. In this study, we proposed an Election Algorithm (EA) to optimize the learning phase of HNN to compensate for the high computational complexity during the learning phase. This research extensively evaluates the proposed model using various performance metrics. The main findings of this research indicated the compatibility and performance of Random 3 Satisfiability logical representation during the learning and retrieval phase via EA with HNN in terms of error evaluations, energy analysis, similarity indices, and variability measures. The results also emphasized that the proposed Random 3 Satisfiability representation incorporates with EA in HNN is capable to optimize the learning and retrieval phase as compared to the conventional model, which deployed Exhaustive Search (ES).
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Gorbenko, A., and V. Popov. "Coevolving solutions of the 3-satisfiability problem." Applied Mathematical Sciences 7 (2013): 603–8. http://dx.doi.org/10.12988/ams.2013.13051.

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Seitz, Sakari, Mikko Alava, and Pekka Orponen. "Focused local search for random 3-satisfiability." Journal of Statistical Mechanics: Theory and Experiment 2005, no. 06 (June 14, 2005): P06006. http://dx.doi.org/10.1088/1742-5468/2005/06/p06006.

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PITTEL, BORIS, and GREGORY B. SORKIN. "The Satisfiability Threshold fork-XORSAT." Combinatorics, Probability and Computing 25, no. 2 (July 31, 2015): 236–68. http://dx.doi.org/10.1017/s0963548315000097.

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We consider ‘unconstrained’ randomk-XORSAT, which is a uniformly random system ofmlinear non-homogeneous equations in$\mathbb{F}$2overnvariables, each equation containingk⩾ 3 variables, and also consider a ‘constrained’ model where every variable appears in at least two equations. Dubois and Mandler proved thatm/n= 1 is a sharp threshold for satisfiability of constrained 3-XORSAT, and analysed the 2-core of a random 3-uniform hypergraph to extend this result to find the threshold for unconstrained 3-XORSAT.We show thatm/n= 1 remains a sharp threshold for satisfiability of constrainedk-XORSAT for everyk⩾ 3, and we use standard results on the 2-core of a randomk-uniform hypergraph to extend this result to find the threshold for unconstrainedk-XORSAT. For constrainedk-XORSAT we narrow the phase transition window, showing thatm − n→ −∞ implies almost-sure satisfiability, whilem − n→ +∞ implies almost-sure unsatisfiability.
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Mansor, Mohd Asyraf, and Saratha Sathasivam. "Accelerating Activation Function for 3- Satisfiability Logic Programming." International Journal of Intelligent Systems and Applications 8, no. 10 (October 8, 2016): 44–50. http://dx.doi.org/10.5815/ijisa.2016.10.05.

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Billionnet, Alain, and Alain Sutter. "An efficient algorithm for the 3-satisfiability problem." Operations Research Letters 12, no. 1 (July 1992): 29–36. http://dx.doi.org/10.1016/0167-6377(92)90019-y.

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Seitz, Sakari, and Pekka Orponen. "An efficient local search method for random 3-satisfiability." Electronic Notes in Discrete Mathematics 16 (October 2003): 71–79. http://dx.doi.org/10.1016/s1571-0653(04)00463-9.

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Porschen, Stefan, Bert Randerath, and Ewald Speckenmeyer. "Exact 3-Satisfiability Is Decidable in Time O(20.16254n )." Annals of Mathematics and Artificial Intelligence 43, no. 1-4 (January 2005): 173–93. http://dx.doi.org/10.1007/s10472-004-9428-x.

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Porschen, Stefan, Bert Randerath, and Ewald Speckenmeyer. "Exact 3-satisfiability is decidable in time O(20.16254n )." Annals of Mathematics and Artificial Intelligence 43, no. 1-4 (December 31, 2004): 173–93. http://dx.doi.org/10.1007/s10472-005-0428-2.

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De Ita Luna, Guillermo, Cristina López Ramírez, and Meliza González Contreras. "Modelling 3-Coloring of Outerplanar Graphs via Incremental Satisfiability." Electronic Notes in Discrete Mathematics 69 (August 2018): 101–8. http://dx.doi.org/10.1016/j.endm.2018.07.014.

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Dissertations / Theses on the topic "3-Satisfiability"

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Aytemiz, Tevfik. "A Probabilistic Study of 3-SATISFIABILITY." Diss., Virginia Tech, 2001. http://hdl.handle.net/10919/28202.

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Discrete optimization problems are defined by a finite set of solutions together with an objective function value assigned to each solution. Local search algorithms provide useful tools for addressing a wide variety of intractable discrete optimization problems. Each such algorithm offers a distinct set of rules to intelligently exploit the solution space with the hope of finding an optimal/near optimal solution using a reasonable amount of computing time. This research studies and analyses randomly generated instances of 3-SATISFIABILITY to gain insights into the structure of the underlying solution space. Two random variables are defined and analyzed to assess the probability that a fixed solution will be assigned a particular objective function value in a randomly generated instance of 3-SATISFIABILITY. Then, a random vector is defined and analyzed to investigate how the solutions in the solution space are distributed over their objective function values. These results are then used to define a stopping criterion for local search algorithms applied to MAX 3-SATISFIABILITY. This research also analyses and compares the effectiveness of two local search algorithms, tabu search and random restart local search, on MAX 3-SATISFIABILITY. Computational results with tabu search and random restart local search on randomly generated instances of 3-SATISFIABILITY are reported. These results suggest that, given a limited computing budget, tabu search offers an effective alternative to random restart local search. On the other hand, these two algorithms yield similar results in terms of the best solution found. The computational results also suggest that for randomly generated instances of 3-SATISFIABILITY (of the same size), the globally optimal solution objective function values are typically concentrated over a narrow range.
Ph. D.
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Hajiaghayi, MohammadTaghi, and Gregory B. Sorkin. "The Satisfiability Threshold of Random 3-SAT Is at Least 3.52." 2003. http://hdl.handle.net/1721.1/30434.

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We prove that a random 3-SAT instance with clause-to-variable densityless than 3.52 is satisfiable with high probability.The proof comes through an algorithm which selects (and sets) a variabledepending on its degree and that of its complement.
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Books on the topic "3-Satisfiability"

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Petke, Justyna. Bridging Constraint Satisfaction and Boolean Satisfiability. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21810-6.

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Sinz, Carsten, and Uwe Egly, eds. Theory and Applications of Satisfiability Testing – SAT 2014. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09284-3.

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Gaspers, Serge, and Toby Walsh, eds. Theory and Applications of Satisfiability Testing – SAT 2017. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66263-3.

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Li, Chu-Min, and Felip Manyà, eds. Theory and Applications of Satisfiability Testing – SAT 2021. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80223-3.

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Pulina, Luca, and Martina Seidl, eds. Theory and Applications of Satisfiability Testing – SAT 2020. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51825-7.

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Heule, Marijn, and Sean Weaver, eds. Theory and Applications of Satisfiability Testing -- SAT 2015. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24318-4.

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Kleine Büning, Hans, and Xishun Zhao, eds. Theory and Applications of Satisfiability Testing – SAT 2008. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-79719-7.

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Kullmann, Oliver, ed. Theory and Applications of Satisfiability Testing - SAT 2009. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02777-2.

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Cimatti, Alessandro, and Roberto Sebastiani, eds. Theory and Applications of Satisfiability Testing – SAT 2012. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31612-8.

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Marques-Silva, João, and Karem A. Sakallah, eds. Theory and Applications of Satisfiability Testing – SAT 2007. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72788-0.

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Book chapters on the topic "3-Satisfiability"

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Rodošek, Robert. "A new approach on solving 3-satisfiability." In Artificial Intelligence and Symbolic Mathematical Computation, 197–212. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-61732-9_59.

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Schiermeyer, Ingo. "Solving 3-satisfiability in less than 1, 579n steps." In Computer Science Logic, 379–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-56992-8_22.

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López-Ramírez, Cristina, Guillermo De Ita, and Alfredo Neri. "Modelling 3-Coloring of Polygonal Trees via Incremental Satisfiability." In Lecture Notes in Computer Science, 93–102. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92198-3_10.

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Schiermeyer, Ingo. "Solving 3—Satisfiability in less than 1,579 n Steps." In Operations Research ’92, 138. Heidelberg: Physica-Verlag HD, 1993. http://dx.doi.org/10.1007/978-3-662-12629-5_39.

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Seitz, Sakari, Mikko Alava, and Pekka Orponen. "Threshold Behaviour of WalkSAT and Focused Metropolis Search on Random 3-Satisfiability." In Theory and Applications of Satisfiability Testing, 475–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11499107_41.

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Hernandez, Nestine Hope S., Richelle Ann B. Juayong, Sherlyne L. Francia, Denise Alyssa A. Francisco, and Henry N. Adorna. "On the Communication Complexity of the Vertex Cover Problem and 3-Satisfiability Problem in ECP Systems." In Membrane Computing, 200–214. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-28475-0_14.

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Zhou, Junping, and Minghao Yin. "The Worst-Case Upper Bound for Exact 3-Satisfiability with the Number of Clauses as the Parameter." In Frontiers in Algorithmics and Algorithmic Aspects in Information and Management, 212–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29700-7_20.

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Vazirani, Vijay V. "Maximum Satisfiability." In Approximation Algorithms, 130–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-04565-7_16.

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Balyo, Tomáš, and Carsten Sinz. "Parallel Satisfiability." In Handbook of Parallel Constraint Reasoning, 3–29. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-63516-3_1.

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Fontaine, Pascal, Mizuhito Ogawa, Thomas Sturm, and Xuan Tung Vu. "Subtropical Satisfiability." In Frontiers of Combining Systems, 189–206. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66167-4_11.

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Conference papers on the topic "3-Satisfiability"

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Chen and Hsieh. "A neural network for 3-satisfiability problems." In International Joint Conference on Neural Networks. IEEE, 1989. http://dx.doi.org/10.1109/ijcnn.1989.118356.

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Mansor, Mohd Asyraf, Saratha Sathasivam, and Mohd Shareduwan Mohd Kasihmuddin. "Post optimization paradigm in maximum 3-satisfiability logic programming." In PROCEEDINGS OF THE 24TH NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES: Mathematical Sciences Exploration for the Universal Preservation. Author(s), 2017. http://dx.doi.org/10.1063/1.4995914.

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Mansor, Mohd Asyraf, Saratha Sathasivam, and Mohd Shareduwan Mohd Kasihmuddin. "3-satisfiability logic programming approach for cardiovascular diseases diagnosis." In PROCEEDING OF THE 25TH NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES (SKSM25): Mathematical Sciences as the Core of Intellectual Excellence. Author(s), 2018. http://dx.doi.org/10.1063/1.5041553.

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Fallah, Farzan, Srinivas Devadas, and Kurt Keutzer. "Functional vector generation for HDL models using linear programming and 3-satisfiability." In the 35th annual conference. New York, New York, USA: ACM Press, 1998. http://dx.doi.org/10.1145/277044.277187.

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Yong-ping, WANG, and XU Dao-yun. "Satisfiability threshold of the strictly d-regular random (3, s)-SAT problem." In 2020 International Conference on Big Data & Artificial Intelligence & Software Engineering (ICBASE). IEEE, 2020. http://dx.doi.org/10.1109/icbase51474.2020.00095.

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Kathirvel, Vigneshwer, Mohd Asyraf Mansor, Mohd Shareduwan Mohd Kasihmuddin, and Saratha Sathasivam. "Performance comparison between exhaustive search and imperialist competitive algorithm for 3-satisfiability programming." In PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MATHEMATICAL SCIENCES AND TECHNOLOGY 2018 (MATHTECH2018): Innovative Technologies for Mathematics & Mathematics for Technological Innovation. AIP Publishing, 2019. http://dx.doi.org/10.1063/1.5136438.

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Abdullahi, Samaila, Mohd Asyraf Mansor, Saratha Sathasivam, Mohd Shareduwan Mohd Kasihmuddin, and Nur Ezlin Binti Zamri. "3-satisfiability reverse analysis method with Hopfield neural network for medical data set." In PROCEEDINGS OF INTERNATIONAL CONFERENCE ON ADVANCES IN MATERIALS RESEARCH (ICAMR - 2019). AIP Publishing, 2020. http://dx.doi.org/10.1063/5.0018141.

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Zhang, Yu-an, Bingfen Li, Qiao Meng, Qiongqiong Hu, and Qinglian Ma. "The experimental analysis of the efficiency of genetic algorithm based on 3-satisfiability problem." In The 2015 11th International Conference on Natural Computation. IEEE, 2015. http://dx.doi.org/10.1109/icnc.2015.7377998.

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Yuan, Zhang, and Li BingFen. "The Empirical Study of the Schema Theory of Genetic Algorithm Based on 3-satisfiability Problem." In 2015 Joint International Mechanical, Electronic and Information Technology Conference. Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/jimet-15.2015.84.

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Carpentieri, Marco. "On robustness of permutations sequencing operators: Solving satisfiability of random 3 — CNFs by simple crossover." In 2011 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2011. http://dx.doi.org/10.1109/cec.2011.5949688.

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