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Optimal Scheduling for Cancer Radiotherapy

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Computers and Mathematical Models in Medicine

Part of the book series: Lecture Notes in Medical Informatics ((LNMED,volume 9))

Abstract

This paper provides a general framework within which one may pose problems of scheduling for treatment regimes with particular reference to optimality. At present, schedules are derived in a purely heuristic fashion. Our mathematical formulation follows the work of Lions and Bensoussan (1) on stock control in which the system is described by a stochastic differential equation and the controls are of impulsive nature. Such controls change the state of the system at instants and by amounts which are available for choice. The minimization of a performance index leads to optimality criteria which can be formulated in terms of quasivariational inequalities for which numerical methods of solutions have recently been developed. (Goursat and Maarek (2)).

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References

  1. J. Lions and A. Bensoussan, “Nouvelles Methodes en Controle Impulsionnel,” Applied Mathematics and Optimisation, 1: 289–312, (1975).

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  2. M. Goursat and G. Maarek, “Nouvelle Approche des problernes de gestion de stocks,” Rapport Laboria, No. 148, I.R.I.A., (1976).

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  3. Mosco and Scarpini, “Complementarity Systems and Approximation of Variational Inequalities, R.A.I.R.O., 83–104,(1975.)

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  4. T. Wheldon and J. Kirk, “Mathematical Derivation of Optimal Treatment Schedules,” British Journal of Radiology, 49: 441–449, (1976).

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  5. J. Fischer,”Mathematical Simulation of Radiation Therapy of Solid Tumours,” Acta, Radiol..Ther.:Phys.Biol, 10: 73–85, (1971).

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  6. K. Alenquist and H. Banks, “A Theoretical and Computational Method for Determining Optimal Treatment Schedules,” Mathematical Biosciences, 29: 159–179, (1976).

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  7. E.M.L. Beale, “On Quadratic Programming,”Nav. Res. Log. Quart., 6: 227, (1958).

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  8. R. Bellman and S. Dreyfus, Applied Dynamic Programming, Princeton University Press, (1962.)

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© 1981 Online Conferences Ltd., Uxbridge, England

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Carmichael, N., Pritchard, A.J. (1981). Optimal Scheduling for Cancer Radiotherapy. In: Cardús, D., Vallbona, C. (eds) Computers and Mathematical Models in Medicine. Lecture Notes in Medical Informatics, vol 9. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-93159-8_17

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  • DOI: https://doi.org/10.1007/978-3-642-93159-8_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-10278-6

  • Online ISBN: 978-3-642-93159-8

  • eBook Packages: Springer Book Archive

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