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1 to 10 of 14 Results
Replication data for "The Hamiltonian p-median Problem: Polyhedral Results and Branch-and-Cut Algorithms"
Mar 13, 2024
Barbato, Michele; Luís Gouveia, 2023, "Replication data for "The Hamiltonian p-median Problem: Polyhedral Results and Branch-and-Cut Algorithms"", https://doi.org/10.13130/RD_UNIMI/UDEATS, UNIMI Dataverse, V3
Dataset containing the experimental results of the research work "The Hamiltonian p-Median Problem: Polyhedral Results and Branch-and-Cut Algorithms".
Replication data for "Sub-tree scheduling for wireless sensor networks with partial coverage: complexity and polynomial-size formulations"
Dec 18, 2023
Barbato, Michele; Bianchessi, Nicola, 2023, "Replication data for "Sub-tree scheduling for wireless sensor networks with partial coverage: complexity and polynomial-size formulations"", https://doi.org/10.13130/RD_UNIMI/GD9OKQ, UNIMI Dataverse, V1
Instances and detailed experimental results of the research work entitled "Sub-tree scheduling for wireless sensor networks with partial coverage: complexity and polynomial-size formulations". For additional information, please refer to the included readme file.
Instances and computational results of: Mathematical Programming for Simultaneous Feature Selection and Outlier Detection under l1 Norm
Sep 27, 2023
Barbato, Michele; Ceselli, Alberto, 2023, "Instances and computational results of: Mathematical Programming for Simultaneous Feature Selection and Outlier Detection under l1 Norm", https://doi.org/10.13130/RD_UNIMI/LZA4F8, UNIMI Dataverse, V1, UNF:6:8qCKYGVl2js4qUPec4qIpg== [fileUNF]
This dataset contains instances and computational results of "Mathematical Programming for Simultaneous Feature Selection and Outlier Detection under l1 Norm". See the included readme files for a description of the dataset content.
Replication data for " On optimally solving sub-tree scheduling for wireless sensor networks with partial coverage: A branch-and-cut algorithm"
Feb 3, 2023
Bianchessi, Nicola, 2023, "Replication data for " On optimally solving sub-tree scheduling for wireless sensor networks with partial coverage: A branch-and-cut algorithm"", https://doi.org/10.13130/RD_UNIMI/IHTWC0, UNIMI Dataverse, V1, UNF:6:o+N3y3vWczdEhAUSUSFb7g== [fileUNF]
This dataset contains new benchmark instances for the optimization problem introduced by Adasme (2019) under the name Sub-Tree Scheduling for Wireless Sensor Networks with Partial Coverage (STSWSN-PC). The instances are those addressed in Bianchessi (2022), in which a complete de...
Technical Report of "Mathematical Programming for Simultaneous Feature Selection and Outlier Detection under l1 Norm"
Jan 3, 2023
Barbato, Michele; Ceselli, Alberto, 2022, "Technical Report of "Mathematical Programming for Simultaneous Feature Selection and Outlier Detection under l1 Norm"", https://doi.org/10.13130/RD_UNIMI/UA8PFI, UNIMI Dataverse, V3
Technical Report of "Mathematical Programming for Simultaneous Feature Selection and Outlier Detection under l1 Norm". Broad experimental campaign. Due to a new implementation, the reported results are outdated. The new results can be found on: https://doi.org/10.13130/RD_UNIMI/L...
Replication Data for: On good encodings for quantum annealing and digital optimization solvers: the cardinality constrained quadratic knapsack case
Dec 27, 2022
PREMOLI, MARCO LUIGI; Alberto Ceselli, 2022, "Replication Data for: On good encodings for quantum annealing and digital optimization solvers: the cardinality constrained quadratic knapsack case", https://doi.org/10.13130/RD_UNIMI/Y3GKUF, UNIMI Dataverse, V1
Replication Data for "On good encodings for quantum annealing and digital optimization solvers: the cardinality constrained quadratic knapsack case". Please refer to file "readme.pdf" for further information about the dataset.
Replication Data for: "Mathematical Programming for Simultaneous Feature Selection and Outlier Detection under l1 Norm"
Oct 26, 2022
Barbato, Michele; Ceselli, Alberto, 2022, "Replication Data for: "Mathematical Programming for Simultaneous Feature Selection and Outlier Detection under l1 Norm"", https://doi.org/10.13130/RD_UNIMI/1MZNNS, UNIMI Dataverse, V1, UNF:6:PWiIzt/vPLfrW/Rq52qghw== [fileUNF]
Training and test instances used in the work "Mathematical Programming for Simultaneous Feature Selection and Outlier Detection under l1 Norm". Several new instances are available at the related datatset available here: https://doi.org/10.13130/RD_UNIMI/LZA4F8
MIPLib Random Decompositions Dataset
Oct 12, 2022
Ceselli, Alberto; Basso, Saverio, 2022, "MIPLib Random Decompositions Dataset", https://doi.org/10.13130/RD_UNIMI/T99WYI, UNIMI Dataverse, V1
The dataset contains a set of about 31000 random decompositions of MIPLib instances, together with (a) an evaluation of a set of 121 features over them (b) bound and time scores, obtained through optimization runs. Their detailed structure is described in the paper: S. Basso, A....
COVID-19 Hospital Resource Management Dataset - Lombardy 2020 - replication data
Jun 7, 2022
Premoli, Marco; Barbato, Michele; Ceselli, Alberto, 2021, "COVID-19 Hospital Resource Management Dataset - Lombardy 2020 - replication data", https://doi.org/10.13130/RD_UNIMI/WWUZIJ, UNIMI Dataverse, V3
This dataset contains realistic instances for the problem "hospital resource management" (HRM), corresponding to the first wave of COVID-19 in Spring 2020 in Lombardy Region (Italy). Refer to file 'SOURCES_FORMULAS_ASSUMPTIONS.pdf' for detailed information about data sources, for...
Replication Data for: Optimized Assignment Patterns in Mobile Edge Cloud Networks
Apr 15, 2022
PREMOLI, MARCO LUIGI; Alberto Ceselli; Marco Fiore; Stefano Secci, 2022, "Replication Data for: Optimized Assignment Patterns in Mobile Edge Cloud Networks", https://doi.org/10.13130/RD_UNIMI/X3VG12, UNIMI Dataverse, V1
Replication data for "Optimized assignment patterns in Mobile Edge Cloud networks." Computers & Operations Research 106 (2019): 246-259. The full description of the dataset is given in the README file.
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