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3-SAT Problem A New Memetic-PSO Algorithm [article]

Nasser Lotfi, Jamshid Tamouk, Mina Farmanbar
2013 arXiv   pre-print
This paper presents a new hybrid evolutionary algorithm for solving this satisfiability problem. 3-SAT problem has the huge search space and hence it is known as a NP-hard problem.  ...  In this paper, we introduce a new evolutionary optimization technique based on PSO, Memetic algorithm and local search approaches.  ...  As described above in Section 1, 3-SAT optimization problem is a NP-hard problem which can be best solved by applying an evolutionary optimization approaches.  ... 
arXiv:1306.5070v1 fatcat:kqgfbw5w45glrgbr6qs4rpk2iu

A Note on Problem Difficulty Measures in Black-Box Optimization: Classification, Realizations and Predictability

Jun He, Colin Reeves, Carsten Witt, Xin Yao
2007 Evolutionary Computation  
Various methods have been defined to measure the hardness of a fitness function for evolutionary algorithms and other black-box heuristics.  ...  Keywords Black-box optimization, evolutionary algorithm, problem difficulty measure, running time, satisfiability problem. c 2007 by the Massachusetts Institute of Technology Evolutionary Computation 15  ...  Acknowledgment An early version of the paper was presented on the PPSN IX Workshop on Evolutionary Algorithms -Bridging Theory and Practice.  ... 
doi:10.1162/evco.2007.15.4.435 pmid:18021014 fatcat:vhxy4y3l5ve67pszowaxuftgki

A superior evolutionary algorithm for 3-SAT [chapter]

Thomas Bäck, Agoston E. Eiben, Marco E. Vink
1998 Lecture Notes in Computer Science  
We study and compare the best heuristic algorithm WGSAT and two evolutionary algorithms, an evolution strategy and an evolutionary algorithm adapting its own tness function while running.  ...  The power of this EA originates from the adaptive mechanism, which is completely problem independent and generally applicable to any constraint satisfaction problem.  ...  Evolutionary Algorithms Evolutionary algorithms have already been applied to 3-SAT by dJS89], FF96], Hao95], and EvdH97]. The bit representation is a natural choice for these EAs.  ... 
doi:10.1007/bfb0040766 fatcat:w6ejoytzlzco7eai5w2y67s2f4

A Clonal Selection Algorithm Based Tabu Search for Satisfiability Problems

Abdesslem Layeb
2012 Journal of Advances in Information Technology  
The underlying idea is to harness the optimization capabilities of clonal selection algorithm to achieve good quality solutions for Max SAT problem.  ...  In order to increase the performance of clonal selection to deal with Max Sat problem, an adaptive fitness function based on weighted clauses has been used.  ...  However, the use of a pure evolutionary algorithm has been unsuccessful in Max Sat problems.  ... 
doi:10.4304/jait.3.2.138-146 fatcat:k7dk33lonnhkbptxsxynasvske

Evolving Variable-Ordering Heuristics for Constrained Optimisation [chapter]

Stuart Bain, John Thornton, Abdul Sattar
2005 Lecture Notes in Computer Science  
In this paper we present and evaluate an evolutionary approach for learning new constraint satisfaction algorithms, specifically for MAX-SAT optimisation problems.  ...  Using four different classes of MAX-SAT problems, we experimentally demonstrate that algorithms evolved with this method exhibit superior performance in comparison to general purpose methods.  ...  Finally, in evaluating the importance of non-linear algorithms, we found them to have better backtrack performance on 10 of the 14 training instances.  ... 
doi:10.1007/11564751_54 fatcat:vnlkftb42bexljl7dhkmpjykty

A Tabu history driven crossover operator design for memetic algorithm applied to Max-2SAT-problems

M. Borschbach, A. Exeler
2008 Proceedings of the 10th annual conference on Genetic and evolutionary computation - GECCO '08  
Simulation performed on several instances of Max-2SAT reference problems are used to evaluate the different memetic algorithm strategies applied in our approach and to compare it to the computational complexity  ...  The solution for the Max-2SAT is the starting point for a selection of these strategies by a brief review.  ...  Among the best exact algorithms is MaxSatz, which won most of the benchmarks for unweighted propositional formula in conjunctive normal form at the Max-SAT evaluation competition 2006.  ... 
doi:10.1145/1389095.1389214 dblp:conf/gecco/BorschbachE08 fatcat:sw7njmk2lnhudjkruqnatbuf2i

Evolutionary Algorithms for the Satisfiability Problem

Jens Gottlieb, Elena Marchiori, Claudio Rossi
2002 Evolutionary Computation  
The key features of successful evolutionary algorithms are identified, thereby providing useful methodological guidelines for designing new heuristics.  ...  An empirical comparison on commonly used benchmarks is presented for the most successful evolutionary algorithms and for WSAT, a prominent local search algorithm for the satisfiability problem.  ...  Evaluation of Evolutionary Algorithms for SAT Empirical Results We compare the algorithms presented in Section 3 on all three benchmark suites that were introduced in Section 4.1.  ... 
doi:10.1162/106365602317301763 pmid:11911782 fatcat:7utbvyuaxnhsvduv7advydznzm

An adaptive evolutionary algorithm for the satisfiability problem

Claudio Rossi, Elena Marchiori, Joost N. Kok
2000 Proceedings of the 2000 ACM symposium on Applied computing - SAC '00  
The results of the experiments indicate th a t this technique is rather successful: it improves on previous approaches based on evolutionary computation and it is competitive with the best heuristic algorithms  ...  This paper introduces an adaptive heuristic-based evolution ary algorithm for the Satisfiability problem (SAT).  ...  EVOLUTIONARY LOCAL SEARCH The idea of integrating evolutionary algorithms with local search techniques has been beneficial for the development of successful evolutionary algorithms for solving hard combina  ... 
doi:10.1145/335603.335912 dblp:conf/sac/RossiMK00 fatcat:cwz2yq7jbvbwdppbf2jsuay4zu

Hyper-Heuristic Based on Iterated Local Search Driven by Evolutionary Algorithm [chapter]

Jiří Kubalík
2012 Lecture Notes in Computer Science  
The performance of the two algorithms was experimentally evaluated on six hard optimization problems using the HyFlex experimental framework [4] and the algorithms were compared with algorithms that took  ...  Two versions of this algorithm, ISEAchesc and ISEA-adaptive, that differ in the re-initialization scheme are presented.  ...  Gabriela Ochoa for kindly providing me with complete outcome data of the ISEA hyper-heuristic calculated for the CHeSC 2011 competition.  ... 
doi:10.1007/978-3-642-29124-1_13 fatcat:vqqxud7ruzfbjo4n77ymiswv2e

MAX-SAT Problem using Hybrid Harmony Search Algorithm

Iyad Abu Doush, Amal Lutfi Quran, Mohammed Azmi Al-Betar, Mohammed A. Awadallah
2017 Journal of Intelligent Systems  
The performance of the proposed approaches is evaluated over standard MAX-SAT benchmarks, and the results are compared with six evolutionary algorithms and three stochastic local search algorithms.  ...  AbstractMaximum Satisfiability problem is an optimization variant of the Satisfiability problem (SAT) denoted as MAX-SAT.  ...  three versions of the proposed HS-based algorithms for MAX 3-SAT are experimentally evaluated and compared with some evolutionary algorithms along with some state-of-the-art MAX 3-SAT solvers.  ... 
doi:10.1515/jisys-2016-0129 fatcat:o22mm5t42ze6jcso5nbhwl4f34

Automated Discovery of Local Search Heuristics for Satisfiability Testing

Alex S. Fukunaga
2008 Evolutionary Computation  
Evolutionary algorithms have previously been applied to directly evolve a solution for a particular SAT instance.  ...  We investigate an evolutionary approach to automating the discovery of new local search heuristics. for SAT.  ...  Finnegan Southey provided valuable clarifications regarding the implementation of the coverage metric measurements.  ... 
doi:10.1162/evco.2008.16.1.31 pmid:18386995 fatcat:2xtt63nr7nf3lolz7lzgg4qosq

A Hybrid Quantum Genetic Algorithm and Local Search based DPLL for Max 3-SAT Problems

Abdesslem Layeb, Djamel-Eddine Saidouni
2014 Applied Mathematics & Information Sciences  
The underlying idea is to harness the optimization capabilities of quantum genetic algorithm to achieve good quality solutions for Max SAT problem.  ...  Unfortunately, this problem has been shown to be NP-hard (non-deterministic polynomial-time hard) if the number of variables per clause is greater than 3.  ...  However, the use of a pure evolutionary algorithm has been unsuccessful in Max Sat problems.  ... 
doi:10.12785/amis/080109 fatcat:qmyh7erwejaovbuaxp4xe4gohi

Hybrid evolutionary algorithms on minimum vertex cover for random graphs

Martin Pelikan, Rajiv Kalapala, Alexander K. Hartmann
2007 Proceedings of the 9th annual conference on Genetic and evolutionary computation - GECCO '07  
This paper analyzes the hierarchical Bayesian optimization algorithm (hBOA) on minimum vertex cover for standard classes of random graphs and transformed SAT instances.  ...  The performance of hBOA is compared with that of the branch-and-bound problem solver (BB), the simple genetic algorithm (GA) and the parallel simulated annealing (PSA).  ...  In this paper we consider the optimization version of minimum vertex cover with the goal of analyzing performance of various evolutionary algorithms and the complete branchand-bound algorithm on this class  ... 
doi:10.1145/1276958.1277073 dblp:conf/gecco/PelikanKH07 fatcat:j5usjs7bkzgrri7hilxamdy3ce

AClib: A Benchmark Library for Algorithm Configuration [chapter]

Frank Hutter, Manuel López-Ibáñez, Chris Fawcett, Marius Lindauer, Holger H. Hoos, Kevin Leyton-Brown, Thomas Stützle
2014 Lecture Notes in Computer Science  
across a distribution of problem instances -Stochastic Optimization -Instances often differ widely in hardness Budget: CPU/wall time vs. # function evaluations -Overheads of configurator count!  ...  types of algorithms -Tree search, local search, metaheuristics, machine learning, … • Large improvements to solvers for many hard combinatorial problems -SAT, MIP, TSP, ASP, time-tabling, AI planning  ... 
doi:10.1007/978-3-319-09584-4_4 fatcat:swnqstpsljhabooaza46k4no4i

A New Primal-Dual Genetic Algorithm: Case Study for the Winner Determination Problem [chapter]

Madalina Raschip, Cornelius Croitoru
2010 Lecture Notes in Computer Science  
This paper presents a new evolutionary computing strategy which uses the linear programming duality information to help the search for optimum solutions of hard optimization problems.  ...  The pursued goal was not to find the best algorithm for solving winner determination problem, but to prove the method's viability using the problem as a case study.  ...  Evolutionary Algorithms are used to tackle hard optimization problems for which classical methods are inappropriate.  ... 
doi:10.1007/978-3-642-12139-5_22 fatcat:de6av4lq5ffbdgns7pg6dttyd4
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