highschool1-aigio

benchmark benchmark_suitable aggregations variable_bound set_partitioning set_packing set_covering cardinality invariant_knapsack equation_knapsack general_linear

Submitter Variables Constraints Density Status Group Objective MPS File
George Fonseca 320404 92568 5.26707e-05 hard timetabling 0 highschool1-aigio.mps.gz

Educational timetabling problems from several real schools/universities around the world. These instances were originally expressed in the xhstt file format [1] and formulated as Integer Programming models as described at [2].

[1] http://www.sciencedirect.com/science/article/pii/S0377221717302242 [2] https://link.springer.com/article/10.1007/s10479-011-1012-2

Instance Statistics

Detailed explanation of the following tables can be found here.

Size Related Properties
Original Presolved
Variables 320404 305241
Constraints 92568 85087
Binaries 319686 304523
Integers 718 718
Continuous 0 0
Implicit Integers 0 190
Fixed Variables 0 0
Nonzero Density 5.26707e-05 5.66134e-05
Nonzeroes 1562170 1470370
Constraint Classification Properties
Original Presolved
Total 92568 85087
Empty 283 0
Free 0 0
Singleton 294 0
Aggregations 5840 5221
Precedence 0 0
Variable Bound 19870 17360
Set Partitioning 17329 18317
Set Packing 9291 9230
Set Covering 532 1512
Cardinality 9153 6890
Invariant Knapsack 10094 7518
Equation Knapsack 18620 17962
Bin Packing 0 0
Knapsack 0 0
Integer Knapsack 0 0
Mixed Binary 0 0
General Linear 1262 1077
Indicator 0 0

Structure

Available nonzero structure and decomposition information. Further information can be found here.

value min median mean max
Components
Constraint %
Variable %
Score

Best Known Solution(s)

No solution available for highschool1-aigio .

Similar instances in collection

The following instances are most similar to highschool1-aigio 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.

Instance Status Variables Binaries Integers Continuous Constraints Nonz. Submitter Group Objective Tags
triptim2 hard 27326 20776 6543 7 14427 521898 MIPLIB submission pool triptim 12.0051 aggregations precedence variable_bound set_partitioning set_packing set_covering cardinality invariant_knapsack general_linear
triptim4 open 27226 18537 8682 7 14361 520532 MIPLIB submission pool triptim 9.8181* aggregations precedence variable_bound set_partitioning set_packing set_covering invariant_knapsack general_linear
triptim1 easy 30055 20456 9592 7 15706 515436 MIPLIB submission pool triptim 22.8680999999999 benchmark benchmark_suitable aggregations precedence variable_bound set_partitioning set_packing set_covering invariant_knapsack general_linear
kottenpark09 open 2893026 2892333 693 0 325547 13085500 George Fonseca timetabling 2120* aggregations precedence variable_bound set_partitioning set_packing set_covering cardinality invariant_knapsack mixed_binary general_linear
kosova1 open 614253 609591 4662 0 304931 3414760 George Fonseca timetabling 526* aggregations precedence variable_bound set_partitioning set_packing set_covering cardinality invariant_knapsack equation_knapsack binpacking general_linear

Reference

@article{FONSECA201728,
title = "Integer programming techniques for educational timetabling",
journal = "European Journal of Operational Research",
volume = "262",
number = "1",
pages = "28 - 39",
year = "2017",
note = "",
issn = "0377-2217",
doi = "http://dx.doi.org/10.1016/j.ejor.2017.03.020",
url = "http://www.sciencedirect.com/science/article/pii/S0377221717302242",
author = "George H.G. Fonseca and Haroldo G. Santos and Eduardo G. Carrano and Thomas J.R. Stidsen",
keywords = "Timetabling",
keywords = "Integer Programming",
keywords = "Formulation"
}

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