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Titlebook: Optimization and Applications; 9th International Co Yury Evtushenko,Milojica Ja?imovi?,Mikhail Posypki Conference proceedings 2019 Springer

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樓主: HAG
21#
發(fā)表于 2025-3-25 05:16:25 | 只看該作者
Minimization of the Weighted Total Sparsity of Cosmonaut Training Coursesw goal function. Training of each cosmonaut is divided into special courses. To avoid too sparse courses, we introduce a special objective function—the weighted total sparsity of training courses. This non-regular objective function requires the development of new methods that differ from methods fo
22#
發(fā)表于 2025-3-25 08:37:47 | 只看該作者
Genetic Local Search for Conflict-Free Minimum-Latency Aggregation Scheduling in Wireless Sensor Netsferred to the sink. During one time slot (time is discrete) each sensor can either send or receive one message or be idle. Moreover, only one message should be sent by each sensor during the aggregation session, and the conflicts caused by interference of radio waves must be excluded. It is require
23#
發(fā)表于 2025-3-25 13:31:35 | 只看該作者
24#
發(fā)表于 2025-3-25 17:34:23 | 只看該作者
Conference proceedings 2019ntenegro, in October 2018.The 35 revised full papers and the one short paper presented were carefully reviewed and selected from 103 submissions. The papers are organized in topical sections on?mathematical programming;?combinatorial and discrete optimization;?optimal control;?optimization in econom
25#
發(fā)表于 2025-3-25 22:37:58 | 只看該作者
26#
發(fā)表于 2025-3-26 00:07:48 | 只看該作者
27#
發(fā)表于 2025-3-26 08:18:55 | 只看該作者
Genetic Local Search for Conflict-Free Minimum-Latency Aggregation Scheduling in Wireless Sensor Netgorithm that uses a genetic algorithm and contains the local search procedures and the randomized mutation procedure. The extensive simulation demonstrates a superiority of our algorithm over the best of the previous approaches.
28#
發(fā)表于 2025-3-26 08:36:37 | 只看該作者
29#
發(fā)表于 2025-3-26 12:47:18 | 只看該作者
30#
發(fā)表于 2025-3-26 17:46:56 | 只看該作者
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