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Titlebook: Optimization in Artificial Intelligence and Data Sciences; ODS, First Hybrid Co Lavinia Amorosi,Paolo Dell’Olmo,Isabella Lari Conference pr

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樓主: McKinley
31#
發(fā)表于 2025-3-27 00:07:56 | 只看該作者
A Fast Heuristic Approach for the Assignment and Sequencing Storage Location Problem Under a Two Led which originates from a real-world application context. We propose a very efficient successive constrained shortest path method, which outperforms a matheuristic approach recently proposed in the literature in terms of both the computational time required and regarding the quality of the solutions
32#
發(fā)表于 2025-3-27 03:02:06 | 只看該作者
Local Search for Aircraft-Landing Planning,while satisfying the . (which imposes minimum threshold times between planes, ranging from 90 to 240 s). In this study, the landing sequence of the planes has to be determined first, and subsequently their associated landing times and . (HSPs) needed to meet such landing times. HSPs consist of makin
33#
發(fā)表于 2025-3-27 09:19:19 | 只看該作者
34#
發(fā)表于 2025-3-27 11:46:09 | 只看該作者
35#
發(fā)表于 2025-3-27 13:44:06 | 只看該作者
Risk Assessment in Transactions Under Threat as Partially Observable Markov Decision Process, under security threats. It is a part of an integrated cybersecurity framework, which combines AI-based planning of active counteractions with Machine Learning for the detection of security threats during transaction processing. The risk assessment is based on the optimal strategy for decision makin
36#
發(fā)表于 2025-3-27 18:48:33 | 只看該作者
37#
發(fā)表于 2025-3-27 23:48:07 | 只看該作者
38#
發(fā)表于 2025-3-28 05:27:33 | 只看該作者
https://doi.org/10.1007/978-3-030-95380-5Operation Research; Discrete optimization; Multiple criteria decision making; Heuristics; Decision makin
39#
發(fā)表于 2025-3-28 09:57:47 | 只看該作者
40#
發(fā)表于 2025-3-28 13:40:40 | 只看該作者
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