메뉴 건너뛰기




Volumn 16, Issue 1, 2008, Pages 31-61

Automated discovery of local search heuristics for satisfiability testing

Author keywords

Constraint satisfaction; Genetic programming; Hybrid genetic local search; Hyper heuristic; SAT; Satisfiability

Indexed keywords

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; EVOLUTION; STATISTICAL MODEL; THEORETICAL MODEL;

EID: 42449117713     PISSN: 10636560     EISSN: 15309304     Source Type: Journal    
DOI: 10.1162/evco.2008.16.1.31     Document Type: Article
Times cited : (111)

References (44)
  • 1
    • 0036784224 scopus 로고    scopus 로고
    • Using genetic programming to learn and improve control knowledge
    • Aler, R., Borrajo, D., and Isasi, P (2002). Using genetic programming to learn and improve control knowledge. Artificial Intelligence, 141(1-2), 29-56.
    • (2002) Artificial Intelligence , vol.141 , Issue.1-2 , pp. 29-56
    • Aler, R.1    Borrajo, D.2    Isasi, P.3
  • 2
    • 33750256074 scopus 로고    scopus 로고
    • Evolving bin packing heuristics with genetic programming
    • Proceedings of the Ninth International Conference on Parallel Problem Solving from Nature PPSN, New York: Springer
    • Burke, E., Hyde, M., and Kendall, G. (2006). Evolving bin packing heuristics with genetic programming. In Proceedings of the Ninth International Conference on Parallel Problem Solving from Nature (PPSN), Lecture Notes in Computer Science Vol. 4193, pp. 860-869. New York: Springer.
    • (2006) Lecture Notes in Computer Science , vol.4193 , pp. 860-869
    • Burke, E.1    Hyde, M.2    Kendall, G.3
  • 3
    • 3042708858 scopus 로고    scopus 로고
    • Hyper-heuristics: An emerging direction in modern search technology
    • Glover, F, and Kochenberger, G, Eds, chap. 16 pp, Dordrecht, The Netherlands: Kluwer
    • Burke, E., Kendall, G., Newall, J., Hart, E., Ross, P., and Schulenburg, S. (2003). Hyper-heuristics: An emerging direction in modern search technology. In Glover, F., and Kochenberger, G. (Eds.), Handbook of Meta-heuristics, chap. 16 (pp. 457-474). Dordrecht, The Netherlands: Kluwer.
    • (2003) Handbook of Meta-heuristics , pp. 457-474
    • Burke, E.1    Kendall, G.2    Newall, J.3    Hart, E.4    Ross, P.5    Schulenburg, S.6
  • 4
    • 84889585310 scopus 로고    scopus 로고
    • A hyperheuristic approach to scheduling a sales summit. In Burke, E., and and Erben, W. (Eds.)
    • Selected Papers of the Third International Conference on the Practice and Theory of Automated Timetabling PATAT 2000
    • Cowling, P., Kendall, G., and Soubeiga, E. (2001). A hyperheuristic approach to scheduling a sales summit. In Burke, E., and and Erben, W. (Eds.), Selected Papers of the Third International Conference on the Practice and Theory of Automated Timetabling (PATAT 2000), Lecture Notes in Computer Science, pp. 176-190.
    • (2001) Lecture Notes in Computer Science , pp. 176-190
    • Cowling, P.1    Kendall, G.2    Soubeiga, E.3
  • 7
    • 0036923148 scopus 로고    scopus 로고
    • Automated discovery of composite SAT variable-selection heuristics
    • Fukunaga, A. (2002). Automated discovery of composite SAT variable-selection heuristics. In Proceedings of the AAAI, pp. 641-648.
    • (2002) Proceedings of the AAAI , pp. 641-648
    • Fukunaga, A.1
  • 9
    • 24644438849 scopus 로고    scopus 로고
    • Evolving local search heuristics for SAT
    • Proc. Genetic and Evolutionary Computation Conference GECCO, of, Berlin: Springer-Verlag
    • Fukunaga, A. (2004b). Evolving local search heuristics for SAT. In Proc. Genetic and Evolutionary Computation Conference (GECCO), Vol. 3103 of Lecture Notes in Computer Science, pp. 483-494. Berlin: Springer-Verlag.
    • (2004) Lecture Notes in Computer Science , vol.3103 , pp. 483-494
    • Fukunaga, A.1
  • 12
    • 0036516407 scopus 로고    scopus 로고
    • Evolutionary algorithms for the satisfiability problem
    • Gottlieb, J., Marchiori, E., and Rossi, C. (2002). Evolutionary algorithms for the satisfiability problem. Evolutionary Computation, 20(1), 35-50.
    • (2002) Evolutionary Computation , vol.20 , Issue.1 , pp. 35-50
    • Gottlieb, J.1    Marchiori, E.2    Rossi, C.3
  • 13
    • 84947906524 scopus 로고    scopus 로고
    • Adaptive fitness functions for the satisfiability problem
    • Proceedings of the Conference on Parallel Problem Solving from Nature, of, Berlin: Springer-Verlag
    • Gottlieb, J., and Voss, N. (2000). Adaptive fitness functions for the satisfiability problem. In Proceedings of the Conference on Parallel Problem Solving from Nature, Vol. 1917 of Lecture Notes in Computer Science, pp. 621-630. Berlin: Springer-Verlag.
    • (2000) Lecture Notes in Computer Science , vol.1917 , pp. 621-630
    • Gottlieb, J.1    Voss, N.2
  • 14
    • 0029679218 scopus 로고    scopus 로고
    • Adaptive problem-solving for large-scale scheduling problems: A case study
    • Gratch, J., and Chien, S. (1996). Adaptive problem-solving for large-scale scheduling problems: A case study. Journal of Artificial Intelligence Research, 4, 365-396.
    • (1996) Journal of Artificial Intelligence Research , vol.4 , pp. 365-396
    • Gratch, J.1    Chien, S.2
  • 16
    • 0032596416 scopus 로고    scopus 로고
    • On the run-time behavior of stochastic local search algorithms for SAT
    • Hoos, H. (1999). On the run-time behavior of stochastic local search algorithms for SAT. In Proceedings of AAAI, pp. 661-666.
    • (1999) Proceedings of AAAI , pp. 661-666
    • Hoos, H.1
  • 17
    • 0342918673 scopus 로고    scopus 로고
    • Local search algorithms for SAT: An empirical evaluation
    • Hoos, H., and Stutzle, T. (2000). Local search algorithms for SAT: An empirical evaluation. Journal of Automated Reasoning, 24, 421-481.
    • (2000) Journal of Automated Reasoning , vol.24 , pp. 421-481
    • Hoos, H.1    Stutzle, T.2
  • 18
    • 0031035643 scopus 로고    scopus 로고
    • An economics approach to hard computational problems
    • Huberman, B., Lukose, R., and Hogg, T. (1997). An economics approach to hard computational problems. Science, 275(5269), 51-54.
    • (1997) Science , vol.275 , Issue.5269 , pp. 51-54
    • Huberman, B.1    Lukose, R.2    Hogg, T.3
  • 22
    • 4344659329 scopus 로고    scopus 로고
    • A study on the use of "self-generation" in memetic algorithms
    • Krasnogor, N., and Gustafson, S. (2004). A study on the use of "self-generation" in memetic algorithms. Natural Computing, 3(1), 53-76.
    • (2004) Natural Computing , vol.3 , Issue.1 , pp. 53-76
    • Krasnogor, N.1    Gustafson, S.2
  • 24
    • 33747046367 scopus 로고    scopus 로고
    • GASAT: A genetic local search algorithm for the satisfiability problem
    • Lardeux, F., Saubion, F., and Hao, J.-K. (2006). GASAT: A genetic local search algorithm for the satisfiability problem. Evolutionary Computation, 24(2), 223-253.
    • (2006) Evolutionary Computation , vol.24 , Issue.2 , pp. 223-253
    • Lardeux, F.1    Saubion, F.2    Hao, J.-K.3
  • 25
    • 33750594458 scopus 로고    scopus 로고
    • A comparison of bloat control methods for genetic programming
    • Luke, S., and Panait, L. (2006). A comparison of bloat control methods for genetic programming. Evolutionary Computation, 24(3), 309-344.
    • (2006) Evolutionary Computation , vol.24 , Issue.3 , pp. 309-344
    • Luke, S.1    Panait, L.2
  • 28
    • 0034154795 scopus 로고    scopus 로고
    • Fitness landscapes, memetic algorithms, and greedy operators for graph bipartitioning
    • Merz, P., and Freisleben, B. (2000). Fitness landscapes, memetic algorithms, and greedy operators for graph bipartitioning. Evolutionary Computation, 8(1), 61-91.
    • (2000) Evolutionary Computation , vol.8 , Issue.1 , pp. 61-91
    • Merz, P.1    Freisleben, B.2
  • 29
    • 0030232147 scopus 로고    scopus 로고
    • Automatically configuring constraint satisfaction problems: A case study
    • Minton, S. (1996). Automatically configuring constraint satisfaction problems: A case study. Constraints, 2(1).
    • (1996) Constraints , vol.2 , Issue.1
    • Minton, S.1
  • 31
    • 0040348129 scopus 로고
    • Strongly typed genetic programming
    • MA: Bolt, Beranek and Newman BBN
    • Montana, D. (1993). Strongly typed genetic programming. Tech. Rep. Cambridge, MA: Bolt, Beranek and Newman (BBN).
    • (1993) Tech. Rep. Cambridge
    • Montana, D.1
  • 35
    • 0035501311 scopus 로고    scopus 로고
    • Local search characteristics of incomplete SAT procedures
    • Schuurmans, D., and Southey, R (2001). Local search characteristics of incomplete SAT procedures. Artificial Intelligence, 132, 121-150.
    • (2001) Artificial Intelligence , vol.132 , pp. 121-150
    • Schuurmans, D.1    Southey, R.2
  • 39
    • 84944321804 scopus 로고    scopus 로고
    • Co-evolution of memetic algorithms: Initial results
    • Proceedings of the Seventh International Conference on Parallel Problem Solving from Nature PPSN, New York: Springer
    • Smith, J. (2002). Co-evolution of memetic algorithms: Initial results. In Proceedings of the Seventh International Conference on Parallel Problem Solving from Nature (PPSN), Lecture Notes in Computer Science Vol. 4193, pp. 537-548. New York: Springer.
    • (2002) Lecture Notes in Computer Science , vol.4193 , pp. 537-548
    • Smith, J.1
  • 42
    • 33750331516 scopus 로고    scopus 로고
    • Clause weighting local search for SAT
    • Thornton, J. (2005). Clause weighting local search for SAT. Journal of Automated Reasoning, 35(1-3), 97-142.
    • (2005) Journal of Automated Reasoning , vol.35 , Issue.1-3 , pp. 97-142
    • Thornton, J.1
  • 43
    • 0037331793 scopus 로고    scopus 로고
    • Effective use of Boolean satisfiability procedures in the formal verification of superscalar and VLIW microprocessors
    • Velev, M., and Bryant, R. (2003). Effective use of Boolean satisfiability procedures in the formal verification of superscalar and VLIW microprocessors. Journal of Symbolic Computation, 35(2), 73-106.
    • (2003) Journal of Symbolic Computation , vol.35 , Issue.2 , pp. 73-106
    • Velev, M.1    Bryant, R.2
  • 44
    • 0003389370 scopus 로고
    • The GENITOR algorithm and selection pressure: Why rank-based allocation of reproductive trials is best
    • Whitley, D. (1989). The GENITOR algorithm and selection pressure: Why rank-based allocation of reproductive trials is best. In Proceedings of the International Conference on Genetic Algorithms (ICGA), pp. 116-121.
    • (1989) Proceedings of the International Conference on Genetic Algorithms (ICGA) , pp. 116-121
    • Whitley, D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.