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pro vyhledávání: '"Chen, Wenbo"'
Recent years have witnessed increasing interest in optimization proxies, i.e., machine learning models that approximate the input-output mapping of parametric optimization problems and return near-optimal feasible solutions. Following recent work by
Externí odkaz:
http://arxiv.org/abs/2405.21023
Optimizing service schedules is pivotal to the reliable, efficient, and inclusive on-demand mobility. This pressing challenge is further exacerbated by the increasing needs of an aging population, the over-subscription of existing services, and the l
Externí odkaz:
http://arxiv.org/abs/2401.03692
The increasing penetration of renewable generation and distributed energy resources requires new operating practices for power systems, wherein risk is explicitly quantified and managed. However, traditional risk-assessment frameworks are not fast en
Externí odkaz:
http://arxiv.org/abs/2310.00709
The load planning problem is a critical challenge in service network design for parcel carriers: it decides how many trailers to assign for dispatch over time between pairs of terminals. Another key challenge is to determine a flow plan, which specif
Externí odkaz:
http://arxiv.org/abs/2307.04050
The paper proposes a novel End-to-End Learning and Repair (E2ELR) architecture for training optimization proxies for economic dispatch problems. E2ELR combines deep neural networks with closed-form, differentiable repair layers, thereby integrating l
Externí odkaz:
http://arxiv.org/abs/2304.11726
Autor:
Chen, Wenbo, Hasegawa, Daniel K., Kaur, Navneet, Kliot, Adi, Pinheiro, Patricia Valle, Luan, Junbo, Stensmyr, Marcus C., Zheng, Yi, Liu, Wenli, Sun, Honghe, Xu, Yimin, Luo, Yuan, Kruse, Angela, Yang, Xiaowei, Kontsedalov, Svetlana, Lebedev, Galina, Fisher, Tonja W., Nelson, David R., Hunter, Wayne B., Brown, Judith K., Jander, Georg, Cilia, Michelle, Douglas, Angela E., Ghanim, Murad, Simmons, Alvin M., Wintermantel, William M., Ling, Kai-Shu, Fei, Zhangjun
Background: The whitefly Bemisia tabaci (Hemiptera: Aleyrodidae) is among the 100 worst invasive species in the world. As one of the most important crop pests and virus vectors, B. tabaci causes substantial crop losses and poses a serious threat to g
Externí odkaz:
http://hdl.handle.net/10150/622601
http://arizona.openrepository.com/arizona/handle/10150/622601
http://arizona.openrepository.com/arizona/handle/10150/622601
The Flexible Job-shop Scheduling Problem (FJSP) is an important combinatorial optimization problem that arises in manufacturing and service settings. FJSP is composed of two subproblems, an assignment problem that assigns tasks to machines, and a sch
Externí odkaz:
http://arxiv.org/abs/2301.09703
This paper reconsiders end-to-end learning approaches to the Optimal Power Flow (OPF). Existing methods, which learn the input/output mapping of the OPF, suffer from scalability issues due to the high dimensionality of the output space. This paper fi
Externí odkaz:
http://arxiv.org/abs/2301.08840
Time series forecasting is a long-standing challenge due to the real-world information is in various scenario (e.g., energy, weather, traffic, economics, earthquake warning). However some mainstream forecasting model forecasting result is derailed dr
Externí odkaz:
http://arxiv.org/abs/2212.01209
Reliability Assessment Commitment (RAC) Optimization is increasingly important in grid operations due to larger shares of renewable generations in the generation mix and increased prediction errors. Independent System Operators (ISOs) also aim at usi
Externí odkaz:
http://arxiv.org/abs/2211.15755