arXiv:2503. 03137v3 Announce Type: replace Abstract: Constructive neural combinatorial optimization (NCO) offers a promising paradigm for solving vehicle routing problems (VRPs) by directly learning to construct approximate optimal solutions, thereby reducing reliance on expert knowledge for algorithm design.
By Changliang Zhou, Xi Lin, Zhenkun Wang, Qingfu Zhang
arXiv:2606. 10431v1 Announce Type: cross Abstract: Multi-task vehicle routing problems play a critical role in enhancing efficiency across various industries and service sectors.
By Shuangchun Gui, Zhiguang Cao, Wen Song, Yew-Soon Ong
arXiv:2608.24859v1 Announce Type: new
Abstract: Multi-task vehicle routing problem (VRP) solvers seek to handle multiple VRP variants within a single unified model, avoiding the need to train a separ...
By Arthur Corr\^ea, Paulo Nascimento, Samuel Moniz
arXiv:2605. 09382v2 Announce Type: replace Abstract: The Linear Assignment Problem is a fundamental combinatorial optimization task where classical exact solvers ensure optimality but suffer from an $\mathcal{O}(N^{3})$ bottleneck, while recent neural approximations struggle with scalability and exactness.
By Ilay Yavlovich, Jad Agbaria, Muhamed Mhamed, Nir Weinberger, Jose Yallouz
Multi-task vehicle routing problems play a critical role in enhancing efficiency across various industries and service sectors. These problems consist of multiple variants that optimize routing costs while meeting diverse customer constraints.
arXiv:2607. 17708v1 Announce Type: new Abstract: Multi-task neural solvers aim to handle multiple Vehicle Routing Problem (VRP) variants within a unified model, avoiding separate training for each constraint combination.
By Yang Wang, Ya-Hui Jia, Wei-Neng Chen, Yi Mei, Wen Song, Zhiguang Cao