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Effects in the Algorithm Performance from Problem Structure, Searching Behavior and Temperature: A Causal Study Case for Threshold Accepting and Bin-Packing

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Computational Science and Its Applications – ICCSA 2019 (ICCSA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11619))

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Abstract

A review of state of art reveals that the characterization and analysis of the relation between problem-algorithm has been focused only on problem features or on algorithm features; or in some situations on both, but the algorithm logical is not considered in the analysis. The above for selecting an algorithm will give the best solution. However there is more knowledge for discovering from this relation. In this paper, significant features are proposed for describing problem structure and algorithm searching fluctuation; other known metrics were considered (Autocorrelation Coefficient and Length) but were not significant. A causal study case is performed for analyzing causes and effects from: Bin-Packing problem structure, Temperature, searching behavior of Threshold Accepting algorithm and final performance to solving problem instances. The proposed features permitted in the causal study to find relations cause-effect; which gave guidelines for designing a Threshold Accepting self-adaptive algorithm. Its performance outperforms to original algorithm in 74% out of 324 problem cases. The causal analysis on relevant information from problem, algorithm (both) and algorithm logical could be an important guideline to discover rules or principles over several problem domains, which permit the design of self-adaptive algorithms to give the best solution to complex problems.

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Authors and Affiliations

  1. Universidad Politécnica de Apodaca (UPAP), Apodaca, Nuevo León, Mexico

    V. Landero & David Ríos

  2. Departamento de Ciencias Computacionales, Centro Nacional de Investigación y Desarrollo Tecnológico (CENIDET), AP 5-164, 62490, Cuernavaca, Mexico

    Joaquín Pérez

  3. División de Estudios de Posgrado e Investigación, Instituto Tecnológico de Ciudad Madero (ITCM), Cd. Madero, Mexico

    L. Cruz

  4. Instituto Tecnológico Superior de Álamo Temapache, Veracruz, Mexico

    Tania Turrubiates

Authors
  1. V. Landero
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  2. Joaquín Pérez
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  3. L. Cruz
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  4. Tania Turrubiates
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  5. David Ríos
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Corresponding author

Correspondence to V. Landero .

Editor information

Editors and Affiliations

  1. Covenant University, Ota, Nigeria

    Sanjay Misra

  2. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  3. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  4. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  5. Saint Petersburg State University, Saint Petersburg, Russia

    Vladimir Korkhov

  6. Polytechnic University of Bari, Bari, Italy

    Carmelo Torre

  7. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  8. Monash University, Clayton, VIC, Australia

    David Taniar

  9. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  10. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

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Landero, V., Pérez, J., Cruz, L., Turrubiates, T., Ríos, D. (2019). Effects in the Algorithm Performance from Problem Structure, Searching Behavior and Temperature: A Causal Study Case for Threshold Accepting and Bin-Packing. In: Misra, S., et al. Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science(), vol 11619. Springer, Cham. https://doi.org/10.1007/978-3-030-24289-3_13

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  • DOI: https://doi.org/10.1007/978-3-030-24289-3_13

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