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Comparison of Evolutionary and Deterministic Multiobjective Algorithms for Dose Optimization in Brachytherapy

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Evolutionary Multi-Criterion Optimization (EMO 2001)

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Abstract

We compare two multiobjective evolutionary algorithms, with deterministic gradient based optimization methods for the dose optimization problem in high-dose rate (HDR) brachytherapy. The optimization considers up to 300 parameters. The objectives are expressed in terms of statistical parameters, from dose distributions. These parameters are approximated from dose values from a small number of points. For these objectives it is known that the deterministic algorithms converge to the global Pareto front. The evolutionary algorithms produce only local Pareto-optimal fronts. The performance of the multiobjective evolutionary algorithms is improved if a small part of the population is initialized with solutions from deterministic algorithms. An explanation is that only a very small part of the search space is close to the global Pareto front. We estimate the performance of the algorithms in some cases in terms of probability compared to a random optimum search method.

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Author information

Authors and Affiliations

  1. Department of Medical Physics and Engineering, Strahlenklinik, Klinikum Offenbach, 63069, Offenbach, Germany

    Natasa Milickovic, Michael Lahanas & Dimos Baltas

  2. Institute of Communication and Computer Systems, National Technical University of Athens, 15773, Zografou, Athens, Greece

    Dimos Baltas & Nikolaos Zamboglou1

Authors
  1. Natasa Milickovic
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  2. Michael Lahanas
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  3. Dimos Baltas
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  4. Nikolaos Zamboglou1
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering Computer Engineering and Networks Laboratory, Swiss Federal Institute of Technology, ETH Zentrum, Gloriastrasse 35, 8092, Zurich, Switzerland

    Eckart Zitzler  & Lothar Thiele  & 

  2. Department of Mechanical Engineering Kanpur Genetic Algorithms Laboratory, Indian Institute of Technology, UP 208 016, Kanpur, India

    Kalyanmoy Deb

  3. Electrical Engineering Department,Computer Science Section Av.Instituto Politecnico Nacional No.2508, CINVESTAV-IPN, Col.San Pedro Zacatenco, 07300, Mexico City, Mexico

    Carlos Artemio Coello Coello

  4. Department of Computer Science, University of Reading, P.O.Box 225, Reading RG6 6AY, Whiteknights, UK

    David Corne

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© 2001 Springer-Verlag Berlin Heidelberg

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Milickovic, N., Lahanas, M., Baltas, D., Zamboglou1, N. (2001). Comparison of Evolutionary and Deterministic Multiobjective Algorithms for Dose Optimization in Brachytherapy. In: Zitzler, E., Thiele, L., Deb, K., Coello Coello, C.A., Corne, D. (eds) Evolutionary Multi-Criterion Optimization. EMO 2001. Lecture Notes in Computer Science, vol 1993. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44719-9_12

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  • DOI: https://doi.org/10.1007/3-540-44719-9_12

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41745-3

  • Online ISBN: 978-3-540-44719-1

  • eBook Packages: Springer Book Archive

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