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2 results for “Mixed-Integer Programming”
SurrogateLIB: An extendable library of mixed-integer programs with embedded machine learning predictors
<p>We constructed a set of Mixed-Integer Programming (MIP) instances with embedded Machine Learning (ML) predictors. The generators for these instances are available at: <a href="https://github.com/Opt-Mucca/PySCIPOpt-ML">https://github.com/Opt-Mucca/PySCIPOpt-ML</a>. The full paper which introduces SurrogateLIB and the larger Python framework PySCIPOpt-ML is available at: <a href="https://arxiv.org/abs/2312.08074">https://arxiv.org/abs/2312.08074</a></p>
Stochastic Mixed-Integer Programming for a Spare Parts Inventory Management Problem
<p>The German Armed Forces provide an operation contingent to support the North Atlantic Treaty Organization (NATO) Response Force (NRF). For short deployments (e.g., one month), the NRF troops can bring with them a tightly constrained "warehouse" of spare parts. To ensure optimal use this warehouse, we developed the computer program "The OPtimization of a Spare Parts INventory" (TOPSPIN) to find an optimal mix of spare parts to repair a set of systems. Each system is composed of several parts, and it can only be used again in the mission if all broken parts are replaced. Due to the stochastic nature of the problem, we generate scenarios that simulate the failure of the parts. The backbone of TOPSPIN is a mixed-integer linear program that determines an optimal, scenario-robust mix of spare parts. Using input data provided by the German Logistikzentrum (RealData.xlsx), we analyze how many scenarios need to be generated in order to determine reliable solutions. A further data set (SimData.xlsx) was generated with random data, having a similar structure as the real data set. Using these two data sets, we analyze the composition of the warehouse over a variety of different weight restrictions, and we examine the number of repairable systems for different values of this bound. </p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.