Improvements to the cluster Newton method for underdetermined inverse problems

• P. Gaudreau ^[1] ; K. Hayami ^[2] ; Y. Aoki ^[3] ; H. Safouhi ^[1] ; A. Konagaya ^[4]
  1. [1] University of Alberta

     University of Alberta

     Canadá

     
  2. [2] Graduate University For Advanced Studies

     Graduate University For Advanced Studies

     Hayama-machi, Japón

     
  3. [3] Uppsala University

     Uppsala University

     Uppsala domkyrkoförs., Suecia

     
  4. [4] Tokyo Institute of Technology

     Tokyo Institute of Technology

     Japón

     

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• Localización: Journal of computational and applied mathematics, ISSN 0377-0427, Vol. 283, Nº 1 (1 August 2015), 2015, págs. 122-141
• Idioma: inglés
• DOI: 10.1016/j.cam.2015.01.014
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• Resumen

  • The Cluster Newton method (CN method) has proved to be very efficient at finding multiple solutions to underdetermined inverse problems. In the case of pharmacokinetics, underdetermined inverse problems are often given extra constraints to restrain the variety of solutions. In this paper, we propose a new algorithm based on the two parameters of the Beta distribution for finding a family of solutions which best fit the extra constraints. This allows for a much greater control on the variety of solutions that can be obtained with the CN method. In addition, this algorithm facilitates the task of obtaining pharmacologically feasible parameters. Moreover, we also make some improvements to the original CN method including an adaptive margin of error for the perturbation of the target values and the use of an analytical Jacobian in the resolution of the forward problem.