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Titlebook: Artificial Evolution; 15th International C Pierrick Legrand,Arnaud Liefooghe,Evelyne Lutton Conference proceedings 2023 The Editor(s) (if a

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41#
發(fā)表于 2025-3-28 18:38:48 | 只看該作者
,Maximizing the?Number of?Satisfied Charging Demands in?Electric Vehicle Charging Scheduling Problem Electric vehicle drivers submit their charging demands. Given the limited resources, these charging demands are either accepted or rejected, and an accepted demand must be satisfied. The objective of the scheduler is to maximize the number of satisfied demands. We prove that the problem is NP-hard.
42#
發(fā)表于 2025-3-28 19:08:50 | 只看該作者
43#
發(fā)表于 2025-3-29 01:20:54 | 只看該作者
44#
發(fā)表于 2025-3-29 03:11:31 | 只看該作者
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發(fā)表于 2025-3-29 08:17:47 | 只看該作者
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發(fā)表于 2025-3-29 12:02:17 | 只看該作者
47#
發(fā)表于 2025-3-29 17:49:25 | 只看該作者
,Designing Attention Based Convolutional Neural Network (CNN) Architectures for?Medical Image Classiaphy (OCT)) is a challenging task due to changing clinical environment and varying noise levels. Manually designing deep learning architectures is a tedious task. However, Neural Architecture Search (NAS) provides the flexibility to automatically search for a suitable architecture for a given proble
48#
發(fā)表于 2025-3-29 20:50:40 | 只看該作者
,A Multi-objective 3D Offline UAV Path Planning Problem with?Variable Flying Altitude,urban environment that is replete with static obstacles. The environment is decomposed into several equal-sized ground cells with an infinite flying altitude. The UAV can adjust the altitude to fly above obstacles or bypass them by choosing another way. Various cells may have different flying risks
49#
發(fā)表于 2025-3-30 00:49:04 | 只看該作者
50#
發(fā)表于 2025-3-30 04:04:02 | 只看該作者
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