Zobrazeno 1 - 10 of 11 pro vyhledávání: '"Anton Bouter"'
2
Obtaining smoothly navigable approximation sets in bi-objective multi-modal optimization
Autor: Renzo J. Scholman, Anton Bouter, Leah R. M. Dickhoff, Tanja Alderliesten, Peter A. N. Bosman
Publikováno v: Lecture Notes in Computer Science ISBN: 9783031147203
Even if a Multi-modal Multi-Objective Evolutionary Algorithm (MMOEA) is designed to find solutions well spread over all locally optimal approximation sets of a Multi-modal Multi-objective Optimization Problem (MMOP), there is a risk that the found se
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a224a2ef7c6cd5c24b342d94d9646b33
https://ir.cwi.nl/pub/32127
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5
GPU-accelerated parallel Gene-pool Optimal Mixing applied to multi-objective Deformable Image Registration
Autor: Anton Bouter, Peter A. N. Bosman, Tanja Alderliesten
Publikováno v: CEC
The Real-Valued Gene-pool Optimal Mixing Evolutionary Algorithm (RV-GOMEA) has previously been successfully used to achieve highly scalable optimization of various real-world problems in a gray-box optimization setting. Deformable Image Registration
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::78ef23a958e3a82b9b9fcd3e2fae9a84
https://doi.org/10.1109/cec45853.2021.9504840
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6
Achieving highly scalable evolutionary real-valued optimization by exploiting partial evaluations
Autor: Anton Bouter, Tanja Alderliesten, Peter A. N. Bosman
Publikováno v: Evolutionary Computation, 29(1), 129-155. MIT Press Journals
Evolutionary Computation, 29(1), 129-155
Evolutionary Computation, 29(1), 129-155. MIT PRESS
It is known that to achieve efficient scalability of an Evolutionary Algorithm (EA), dependencies (also known as linkage) must be properly taken into account during variation. In a Gray-Box Optimization (GBO) setting, exploiting prior knowledge regar
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6bad8b8ca044c31cdae47ad0d84408f0
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85101967204&origin=inward
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7
GPU‐accelerated bi‐objective treatment planning for prostate high‐dose‐rate brachytherapy
Autor: Tanja Alderliesten, Bradley R. Pieters, Anton Bouter, Peter A. N. Bosman, Arjan Bel, Yury Niatsetski
Publikováno v: Medical physics, 46(9), 3776-3787. AAPM-American Association of Physicists in Medicine
Medical Physics, 46(9), 3776-3787. AAPM-American Association of Physicists in Medicine
Medical Physics, 46(9), 3776-3787
Bouter, A, Alderliesten, T, Pieters, B R, Bel, A, Niatsetski, Y & Bosman, P A N 2019, ' GPU-accelerated bi-objective treatment planning for prostate high-dose-rate brachytherapy ', Medical Physics, vol. 46, no. 9, pp. 3776-3787 . https://doi.org/10.1002/mp.13681
Purpose: The purpose of this study is to improve upon a recently introduced bi-objective treatment planning method for prostate high-dose-rate (HDR) brachytherapy (BT), both in terms of resulting plan quality and runtime requirements, to the extent t
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1146a16005128f774ba8dae628ce8688
https://doi.org/10.1002/mp.13681
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8
Fitness-based linkage learning in the Real-Valued Gene-pool Optimal Mixing Evolutionary Algorithm
Autor: Anton Bouter, Chantal Olieman, Peter A. N. Bosman
Publikováno v: IEEE Transactions on Evolutionary Computation, 25(2), 358-370
IEEE Transactions on Evolutionary Computation, 25(2)
The recently introduced real-valued gene-pool optimal mixing evolutionary algorthm (RV-GOMEA) has been shown to be among the state of the art for solving gray-box optimization problems where partial evaluations can be leveraged. A core strength is it
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eaca2b8f2696ef9ce361ca5cfa3943a7
https://ir.cwi.nl/pub/30301
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9
Leveraging conditional linkage models in gray-box optimization with the real-valued gene-pool optimal mixing evolutionary algorithm
Autor: Anton Bouter, Tanja Alderliesten, S. C. Maree, Peter A. N. Bosman
Publikováno v: GECCO
GECCO 2020-Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 603-611
STARTPAGE=603;ENDPAGE=611;TITLE=GECCO 2020-Proceedings of the 2020 Genetic and Evolutionary Computation Conference
GECCO 2020: Proceedings of the 2020 Genetic and Evolutionary Computation Conference
GECCO 2020
Often, real-world problems are of the gray-box type. It has been shown that the Real-Valued Gene-pool Optimal Mixing Evolutionary Algorithm (RV-GOMEA) is in principle capable of exploiting such a Gray-Box Optimization (GBO) setting using linkage mode
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::91a65de9674a66bd087f374e1703d006
https://doi.org/10.1145/3377930.3390225
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10
Large-scale parallelization of partial evaluations in evolutionary algorithms for real-world problems
Autor: Anton Bouter, Arjan Bel, Tanja Alderliesten, Cees Witteveen, Peter A. N. Bosman
Publikováno v: GECCO 2018-Proceedings of the 2018 Genetic and Evolutionary Computation Conference, 1199-1206
STARTPAGE=1199;ENDPAGE=1206;TITLE=GECCO 2018-Proceedings of the 2018 Genetic and Evolutionary Computation Conference
GECCO
The importance and potential of Gray-Box Optimization (GBO) with evolutionary algorithms is becoming increasingly clear lately, both for benchmark and real-world problems. We consider the GBO setting where partial evaluations are possible, meaning th
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b86bb7f032c50e5666b8a17c0fd377ae
https://ir.cwi.nl/pub/27890
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