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Volumn 7997 LNCS, Issue , 2013, Pages 410-422

Tuning algorithms for tackling large instances: An experimental protocol

Author keywords

Automatic algorithm configuration; Iterated local search; Quadratic assignment problem; Robust tabu search; Scaling of parameters

Indexed keywords

ALGORITHM PARAMETERS; AUTOMATIC ALGORITHMS; EXPERIMENTAL PROTOCOLS; ITERATED LOCAL SEARCH; QUADRATIC ASSIGNMENT PROBLEMS; SCALING OF PARAMETERS; STOCHASTIC LOCAL SEARCHES; TABU SEARCH ALGORITHMS;

EID: 84890952869     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-44973-4_44     Document Type: Conference Paper
Times cited : (9)

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  • 6
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    • Comparison of iterative searches for the quadratic assignment problem
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  • 8
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    • Multiple trajectory search for large scale global optimization
    • Piscataway, NJ, IEEE, June
    • Tseng, L.Y., Chen, C.: Multiple trajectory search for large scale global optimization. In: Proceedings of IEEE Congress on Evolutionary Computation, Piscataway, NJ, IEEE, pp. 3052-3059 June 2008
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    • Tseng, L.Y.1    Chen, C.2
  • 9
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    • Towards a theory of practice in metaheuristics design: A machine learning perspective
    • Birattari, M., Zlochin, M., Dorigo, M.: Towards a theory of practice in metaheuristics design: a machine learning perspective. Theor. Inform. Appl. 40(2), 353-369 (2006)
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    • Automatically configuring algorithms for scaling performance
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.