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Evaluation of Elite Athletes Training Management Efficiency Based on Multiple Criteria Measure of Conditioning Using Fewer Data

Author

Listed:
  • Aleksandras Krylovas

    (Department of Mathematical Modelling, Vilnius Gediminas Technical University, Saulėtekio al. 11, 10221 Vilnius, Lithuania)

  • Natalja Kosareva

    (Department of Mathematical Modelling, Vilnius Gediminas Technical University, Saulėtekio al. 11, 10221 Vilnius, Lithuania)

  • Rūta Dadelienė

    (Department of Rehabilitation, Physical and Sports Medicine, Institute of Health Science, Vilnius University, Saulėtekio al. 11, 10221 Vilnius, Lithuania)

  • Stanislav Dadelo

    (Department of Entertainment Industries, Vilnius Gediminas Technical University, Saulėtekio al. 11, 10221 Vilnius, Lithuania)

Abstract

Innovative solutions and techniques in the sports industry are commonly used and tested in real conditions. Elite athletes have to achieve their peak performance before the main competition of the year, which is the World Championship, and every fourth year before the Olympic Games, when the main competition of athletes takes place. The present study aims to analyze and evaluate the ability of elite kayakers to achieve the best form at the right times, with the Olympic Games taking the greatest importance. Target values for multiple measures of conditioning are compared to target values set by experts. A weighted least squares metric with weights varied by time period is developed as a measure of fulfillment of the athletes’ conditioning plans. The novelty of the paper is the idea of using linear combination of polynomials and trigonometric functions for approximating the target functions and application of the proposed methodology for the optimization and evaluation of athletic training.

Suggested Citation

  • Aleksandras Krylovas & Natalja Kosareva & Rūta Dadelienė & Stanislav Dadelo, 2020. "Evaluation of Elite Athletes Training Management Efficiency Based on Multiple Criteria Measure of Conditioning Using Fewer Data," Mathematics, MDPI, vol. 8(1), pages 1-17, January.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:1:p:66-:d:304532
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    References listed on IDEAS

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    1. Rodolphe Durand & Robert M. Grant & Tammy L. Madsen & Rodolphe Durand & Robert M. Grant & Tammy L. Madsen, 2017. "The expanding domain of strategic management research and the quest for integration," Strategic Management Journal, Wiley Blackwell, vol. 38(1), pages 4-16, January.
    2. Laengle, Sigifredo & Merigó, José M. & Miranda, Jaime & Słowiński, Roman & Bomze, Immanuel & Borgonovo, Emanuele & Dyson, Robert G. & Oliveira, José Fernando & Teunter, Ruud, 2017. "Forty years of the European Journal of Operational Research: A bibliometric overview," European Journal of Operational Research, Elsevier, vol. 262(3), pages 803-816.
    3. Aleksandras Krylovas & Stanislavas Dadelo & Natalja Kosareva & Edmundas Kazimieras Zavadskas, 2017. "Entropy–KEMIRA Approach for MCDM Problem Solution in Human Resources Selection Task," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(05), pages 1183-1209, September.
    4. Dariush Khezrimotlagh & Yao Chen, 2018. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Decision Making and Performance Evaluation Using Data Envelopment Analysis, chapter 0, pages 217-234, Springer.
    5. Sivarajah, Uthayasankar & Kamal, Muhammad Mustafa & Irani, Zahir & Weerakkody, Vishanth, 2017. "Critical analysis of Big Data challenges and analytical methods," Journal of Business Research, Elsevier, vol. 70(C), pages 263-286.
    6. Karsu, Özlem & Morton, Alec, 2014. "Incorporating balance concerns in resource allocation decisions: A bi-criteria modelling approach," Omega, Elsevier, vol. 44(C), pages 70-82.
    7. Reefke, Hendrik & Sundaram, David, 2017. "Key themes and research opportunities in sustainable supply chain management – identification and evaluation," Omega, Elsevier, vol. 66(PB), pages 195-211.
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