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Note on “A chance-constrained programming framework to handle uncertainties in radiation therapy treatment planning”

Author

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  • Custodio, Janiele
  • Lejeune, Miguel
  • Zavaleta, Antonio

Abstract

A recent article by Zaghian et al. (2018) proposed reformulations, proposed reformulations of stochastic chance-constrained programming models for radiation therapy treatment planning. This note questions the validity of the proposed reformulations and shows that they are not equivalent to the original formulations. Two numerical examples illustrate that the approach proposed by Zaghian et al. (2018) provides approximation problems and not reformulations.

Suggested Citation

  • Custodio, Janiele & Lejeune, Miguel & Zavaleta, Antonio, 2019. "Note on “A chance-constrained programming framework to handle uncertainties in radiation therapy treatment planning”," European Journal of Operational Research, Elsevier, vol. 275(2), pages 793-794.
    • Handle: RePEc:eee:ejores:v:275:y:2019:i:2:p:793-794
    DOI: 10.1016/j.ejor.2018.11.071
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    References listed on IDEAS

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    1. Zaghian, Maryam & Lim, Gino J. & Khabazian, Azin, 2018. "A chance-constrained programming framework to handle uncertainties in radiation therapy treatment planning," European Journal of Operational Research, Elsevier, vol. 266(2), pages 736-745.
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