Zobrazeno 1 - 10
of 759
pro vyhledávání: '"Van Hentenryck, P."'
Transmission Expansion Planning (TEP) is the process of optimizing the development and upgrade of the power grid to ensure reliable, efficient, and cost-effective electricity delivery while addressing grid constraints. To support growing demand and r
Externí odkaz:
http://arxiv.org/abs/2412.03799
This study develops a deep learning-based approach to automate inbound load plan adjustments for a large transportation and logistics company. It addresses a critical challenge for the efficient and resilient planning of E-commerce operations in pres
Externí odkaz:
http://arxiv.org/abs/2411.17502
This chapter is meant to be part of the book "Differential Privacy in Artificial Intelligence: From Theory to Practice" and provides an introduction to Differential Privacy. It starts by illustrating various attempts to protect data privacy, emphasiz
Externí odkaz:
http://arxiv.org/abs/2411.04710
This paper addresses the incompatible case of parallel batch scheduling, where compatible jobs belong to the same family, and jobs from different families cannot be processed together in the same batch. Existing constraint programming (CP) models for
Externí odkaz:
http://arxiv.org/abs/2410.11981
The integration of renewable energy sources (RES) into power grids presents significant challenges due to their intrinsic stochasticity and uncertainty, necessitating the development of new techniques for reliable and efficient forecasting. This pape
Externí odkaz:
http://arxiv.org/abs/2409.07637
The paper studies a large-scale order fulfillment problem for a leading e-commerce company in the United States. The challenge involves selecting fulfillment centers and shipping carriers with observational data only to efficiently process orders fro
Externí odkaz:
http://arxiv.org/abs/2409.06918
Autor:
Kotary, James, Di Vito, Vincenzo, Cristopher, Jacob, Van Hentenryck, Pascal, Fioretto, Ferdinando
The Predict-Then-Optimize framework uses machine learning models to predict unknown parameters of an optimization problem from exogenous features before solving. This setting is common to many real-world decision processes, and recently it has been s
Externí odkaz:
http://arxiv.org/abs/2409.04898
Most US school districts draw geographic "attendance zones" to assign children to schools based on their home address, a process that can replicate existing neighborhood racial/ethnic and socioeconomic status (SES) segregation in schools. Redrawing b
Externí odkaz:
http://arxiv.org/abs/2408.12572
Autor:
Chai, Sheng, Chadney, Gus, Avery, Charlot, Grunewald, Phil, Van Hentenryck, Pascal, Donti, Priya L.
Access to granular demand data is essential for the net zero transition; it allows for accurate profiling and active demand management as our reliance on variable renewable generation increases. However, public release of this data is often impossibl
Externí odkaz:
http://arxiv.org/abs/2407.11785
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