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1 to 8 of 8 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.
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...
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.
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 "Exact Algorithms for Maximum Lifetime Data-Gathering Tree in Wireless Sensor Networks"
Jan 11, 2022
Ceselli, Alberto; Casazza, Marco, 2022, "Replication data for "Exact Algorithms for Maximum Lifetime Data-Gathering Tree in Wireless Sensor Networks"", https://doi.org/10.13130/RD_UNIMI/VHW2QV, UNIMI Dataverse, V1, UNF:6:U/L+h6e36wYpccCRTD5/Rg== [fileUNF]
Dataset of instances used in the paper "Exact algorithms for Maximum Lifetime Data Gathering Tree in Wireless Sensors Networks". The repository contains two folders (CCD and ZTD) corresponding to the instances used in the paper. Their full description is given in two README files...
Replication data for "Dantzig–Wolfe reformulations for binary quadratic problems" - kQKP dataset
Jul 27, 2021
Ceselli, Alberto; Létocart, Lucas; Traversi, Emiliano, 2021, "Replication data for "Dantzig–Wolfe reformulations for binary quadratic problems" - kQKP dataset", https://doi.org/10.13130/RD_UNIMI/3QA23K, UNIMI Dataverse, V1
The dataset contains instances for the cardinality constrained quadratic knapsack problem. These are used to test decomposition methods for Binary Quadratic Programs. Full details are given in the corresponding paper "Dantzig-Wolfe Reformulations for Binary Quadratic Problems "....
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