Replication data for "Dantzig–Wolfe reformulations for binary quadratic problems" - kQKP datasetdoi:10.13130/RD_UNIMI/3QA23KUNIMI Dataverse2021-07-271Ceselli, 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, V1Replication data for "Dantzig–Wolfe reformulations for binary quadratic problems" - kQKP datasetdoi:10.13130/RD_UNIMI/3QA23KCeselli, AlbertoLétocart, LucasTraversi, EmilianoUNIMI DataverseCeselli, AlbertoCeselli, Alberto2021-07-27Computer and Information ScienceMathematical SciencesMathematical programmingdecomposition methodsThe 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 ". The dataset contains three sets of instances
- qcr_instances: base instance, together with the optimal quadratic convex reformulation (QCR) multipliers found by solving an associated semidefinite program
- mqcr_instances: base instance, together with the optimal improved convex 0-1 quadratic program reformulation (MQCR) multipliers found by solving an associated semidefinite program
- convexity_analysis: instances in which the objective function quadratic cost matrix has a given number of positive eigenvalues.Ceselli, A., Létocart, L. & Traversi, E. Dantzig–Wolfe reformulations for binary quadratic problems. Math. Prog. Comp. 14, 85–120 (2022). https://doi.org/10.1007/s12532-021-00206-wconvexity_analysis.tgzBase instances, together with QCR multipliers. Data is given in folders, of the form <perc. of positive eigenvalues>_<matrix density>_<instance_size>. Each folder contains ten subfolders, one for each instance.application/x-compressed-tarmqcr_instances.tgzBase instances, together with MQCR multipliers. Data is given in folders, of the form <matrix density>_<instance_size>. Each folder contains ten subfolders, one for each instance.application/x-compressed-tarqcr_instances.tgzBase instances, together with QCR multipliers. Data is given in folders, of the form <matrix density>_<instance_size>. Each folder contains ten subfolders, one for each instance.application/x-compressed-tar