Submitter | Variables | Constraints | Density | Status | Group | Objective | MPS File |
---|---|---|---|---|---|---|---|
Harald Schilly | 7901 | 14163 | 7.3661e-04 | easy | lectsched | 4 | lectsched-4-obj.mps.gz |
University lecture scheduling instance Imported from MIPLIB2010.
Detailed explanation of the following tables can be found here.
Original | Presolved | |
---|---|---|
Variables | 7901 | 3051 |
Constraints | 14163 | 5345 |
Binaries | 7665 | 2937 |
Integers | 236 | 114 |
Continuous | 0 | 0 |
Implicit Integers | 0 | 0 |
Fixed Variables | 0 | 0 |
Nonzero Density | 0.00073661 | 0.00155615 |
Nonzeroes | 82428 | 25377 |
Original | Presolved | |
---|---|---|
Total | 14163 | 5345 |
Empty | 0 | 0 |
Free | 0 | 0 |
Singleton | 894 | 0 |
Aggregations | 2 | 2 |
Precedence | 35 | 43 |
Variable Bound | 60 | 386 |
Set Partitioning | 0 | 0 |
Set Packing | 0 | 0 |
Set Covering | 0 | 1 |
Cardinality | 0 | 0 |
Invariant Knapsack | 0 | 0 |
Equation Knapsack | 0 | 0 |
Bin Packing | 0 | 0 |
Knapsack | 0 | 0 |
Integer Knapsack | 1336 | 258 |
Mixed Binary | 0 | 0 |
General Linear | 11836 | 4655 |
Indicator | 0 | 0 |
Available nonzero structure and decomposition information. Further information can be found here.
Decomposed structure of original problem (dec-file)
Decomposed structure after trivial presolving (dec-file)
value | min | median | mean | max | |
---|---|---|---|---|---|
Components | 1.623249 | ||||
Constraint % | 0.0188359 | 1.326330 | 0.0188359 | 47.2029 | |
Variable % | 0.0431593 | 0.928977 | 0.0431593 | 32.3479 | |
Score | 0.388501 |
Find solutions below. Download the archive containing all solutions from the Download page.
ID | Objective | Exact | Int. Viol | Cons. Viol | Obj. Viol | Submitter | Date | Description |
---|---|---|---|---|---|---|---|---|
2 | 4 | 4 | 0 | 0 | 0 | - | 2018-10-12 | Solution found during MIPLIB2017 problem selection. |
1 | 4 | 4 | 0 | 0 | 0 | - | 2018-10-12 | Solution imported from MIPLIB2010. |
The following instances are most similar to lectsched-4-obj in the collection. This similarity analysis is based on 100 scaled instance features describing properties of the variables, objective function, bounds, constraints, and right hand sides.
@mastersthesis{Schilly2007,
author = {Harald Schilly},
language = {german},
school = {Universit{\"a}t Wien},
title = {Modellierung und {I}mplementation eines {V}orlesungsplaners},
type = {Diploma thesis},
year = {2007}
}