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Volumn , Issue , 2009, Pages 784-791

Stochastic offline programming

Author keywords

[No Author keywords available]

Indexed keywords

AVERAGE-CASE; COMBINATORIAL ALGORITHM; OFF LINE PROGRAMMING; OFF-LINE LEARNING; OPTIMAL SOLUTIONS; SPECIFIC DISTRIBUTION;

EID: 77949584736     PISSN: 10823409     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICTAI.2009.23     Document Type: Conference Paper
Times cited : (9)

References (16)
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  • 2
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    • A dynamic subgradient-based branch-and-bound procedure for set covering
    • E. Balas and M. Carrera. A dynamic subgradient-based branch-and-bound procedure for set covering. Operations Research, 44:875-890, 1996.
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    • Balas, E.1    Carrera, M.2
  • 5
    • 24044449704 scopus 로고    scopus 로고
    • Learning Evaluation Functions to Improve Optimization by Local Search
    • J.A. Boyan and A.W. Moore. Learning Evaluation Functions to Improve Optimization by Local Search. Journal of Machine Learning Research, 1:77-112, 2000.
    • (2000) Journal of Machine Learning Research , vol.1 , pp. 77-112
    • Boyan, J.A.1    Moore, A.W.2
  • 6
    • 0035128384 scopus 로고    scopus 로고
    • Using Experimental Design to Find Effective Parameter Settings for Heuristics
    • S.P. Coy, B.L. Golden, G.C. Runger, E.A. Wasil. Using Experimental Design to Find Effective Parameter Settings for Heuristics. Journal of Heuristics, 7(1):77-97, 2001.
    • (2001) Journal of Heuristics , vol.7 , Issue.1 , pp. 77-97
    • Coy, S.P.1    Golden, B.L.2    Runger, G.C.3    Wasil, E.A.4
  • 7
    • 42449117713 scopus 로고    scopus 로고
    • Automated discovery of local search heuristics for satisfiability testing
    • A. Fukunaga. Automated discovery of local search heuristics for satisfiability testing. Evolutionary Computation, 16(1):31-61, 2008.
    • (2008) Evolutionary Computation , vol.16 , Issue.1 , pp. 31-61
    • Fukunaga, A.1
  • 9
    • 36348984418 scopus 로고    scopus 로고
    • Automatic Algorithm Configuration based on Local Search
    • F. Hutter, H. Hoos, T. Stuetzle. Automatic Algorithm Configuration based on Local Search. AAAI, 1152-1157, 2007.
    • (2007) AAAI , vol.1152-1157
    • Hutter, F.1    Hoos, H.2    Stuetzle, T.3
  • 10
    • 0003841602 scopus 로고    scopus 로고
    • Why the logistic function? A tutorial discussion on probabilities and neural networks
    • M. Jordan. Why the logistic function? A tutorial discussion on probabilities and neural networks. MIT Computational Cognitive Science Report, 9503:1995.
    • MIT Computational Cognitive Science Report , pp. 9503-1995
    • Jordan, M.1
  • 12
    • 0030232147 scopus 로고    scopus 로고
    • Automatically Configuring Constraint Satisfaction Programs
    • S. Minton. Automatically Configuring Constraint Satisfaction Programs. Constraints, 1(1):1-40, 1996.
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  • 13
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    • Understanding Random SAT: Beyond the Clauses-to-Variables Ratio
    • E. Nudelman, K. Leyton-Brown, H.H. Hoos, A. Devkar, Y. Shoham. Understanding Random SAT: Beyond the Clauses-to-Variables Ratio. CP, 438-452, 2004.
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    • Nudelman, E.1    Leyton-Brown, K.2    Hoos, H.H.3    Devkar, A.4    Shoham, Y.5
  • 15
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    • Impact-Based Search Strategies for Constraint Programming
    • Ph. Refalo. Impact-Based Search Strategies for Constraint Programming. CP, pp. 557-571, 2004.
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    • R. Wunderling. Paralleler und objektorientierter Simplex-Algorithmus Technische Universität Berlin, 1996.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.