终点 发表于 2025-3-23 13:38:09
http://reply.papertrans.cn/25/2424/242392/242392_11.pngneolith 发表于 2025-3-23 16:46:46
Additional Research Lines Concerning CMSA,d instead of an integer linear programming solver for sub-instance solving. Following an examination that elucidates the relationship between large neighborhood search and CMSA, the chapter wraps up by underscoring promising avenues for future research.注意 发表于 2025-3-23 21:07:17
https://doi.org/10.1007/978-1-349-05806-8 already used for the illustration of other CMSA variants in previous chapters. In particular, applications to the Minimum Dominating Set (MDS) problem and the Far From Most String (FFMS) problem are presented.残忍 发表于 2025-3-23 22:57:27
http://reply.papertrans.cn/25/2424/242392/242392_14.pngHemiplegia 发表于 2025-3-24 06:07:04
Properties and Mechanics of Solids,ssible to simply eliminate certain values from these domains. In this chapter, we present an illustration of CMSA applied to a combinatorial optimization problem naturally formulated as a non-binary ILP. Specifically, we make use of the Bounded Knapsack Problem with Conflicts.混合物 发表于 2025-3-24 10:18:17
Adding Learning to CMSA, already used for the illustration of other CMSA variants in previous chapters. In particular, applications to the Minimum Dominating Set (MDS) problem and the Far From Most String (FFMS) problem are presented.闹剧 发表于 2025-3-24 12:00:49
Replacing Hard Mathematical Models with Set Covering Formulations,e Windows and Simultaneous Pickups and Deliveries (EVRP-TW-SPD). In both applications, CMSA based on a set covering model significantly outperforms CMSA when using an assignment-type model. Moreover, state-of-the-art results are obtained for both considered optimization problems.涂掉 发表于 2025-3-24 17:08:36
http://reply.papertrans.cn/25/2424/242392/242392_18.pngfloodgate 发表于 2025-3-24 22:55:31
http://reply.papertrans.cn/25/2424/242392/242392_19.png震惊 发表于 2025-3-25 00:27:43
Book 2024ctory chapter about standard CMSA, subsequent chapters cover a self-adaptive CMSA variant as well as a variant equipped with a learning component for improving the quality of the generated solutions over time. Furthermore, on outlining the advantages of using set-covering-based integer linear progra