Learning and Intelligent Optimization
14th International Conference, LION 14, Athens, Greece, May 24-28, 2020, Revised Selected Papers
Herausgegeben: Kotsireas, Ilias S.; Pardalos, Panos M.
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This book constitutes the refereed post-conference proceedings on Learning and Intelligent Optimization, LION 14, held in Athens, Greece, in May 2020. The 37 full papers presented together with one invited paper have been carefully reviewed and selected from 75 submissions. LION deals with designing and engineering ways of "learning" about the performance of different techniques, and ways of using past experience about the algorithm behavior to improve performance in the future. Intelligent learning schemes for mining the knowledge obtained online or offline can improve the algorithm design p...
This book constitutes the refereed post-conference proceedings on Learning and Intelligent Optimization, LION 14, held in Athens, Greece, in May 2020.
The 37 full papers presented together with one invited paper have been carefully reviewed and selected from 75 submissions. LION deals with designing and engineering ways of "learning" about the performance of different techniques, and ways of using past experience about the algorithm behavior to improve performance in the future. Intelligent learning schemes for mining the knowledge obtained online or offline can improve the algorithm design process and simplify the applications of high-performance optimization methods. Combinations of different algorithms can further improve the robustness and performance of the individual components.
Due to the COVID-19 pandemic, LION 14 was not held as a physical meeting.
The 37 full papers presented together with one invited paper have been carefully reviewed and selected from 75 submissions. LION deals with designing and engineering ways of "learning" about the performance of different techniques, and ways of using past experience about the algorithm behavior to improve performance in the future. Intelligent learning schemes for mining the knowledge obtained online or offline can improve the algorithm design process and simplify the applications of high-performance optimization methods. Combinations of different algorithms can further improve the robustness and performance of the individual components.
Due to the COVID-19 pandemic, LION 14 was not held as a physical meeting.
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