hgms62

aggregations variable_bound set_partitioning set_packing set_covering invariant_knapsack equation_knapsack mixed_binary

Submitter Variables Constraints Density Status Group Objective MPS File
Jesus Rodriguez 48597 582237 6.19629e-05 open hgms -44837.24534313961* hgms62.mps.gz

Maintenance scheduling of generators in hydropower systems

Instance Statistics

Detailed explanation of the following tables can be found here.

Size Related Properties
Original Presolved
Variables 48597 44730
Constraints 582237 577169
Binaries 547 524
Integers 0 0
Continuous 48050 44206
Implicit Integers 0 0
Fixed Variables 3844 0
Nonzero Density 6.19629e-05 5.48082e-05
Nonzeroes 1753240 1414970
Constraint Classification Properties
Original Presolved
Total 582237 577169
Empty 0 0
Free 0 0
Singleton 49 0
Aggregations 1478 1478
Precedence 0 0
Variable Bound 18294 334015
Set Partitioning 65 65
Set Packing 36 36
Set Covering 8 8
Cardinality 0 0
Invariant Knapsack 54 52
Equation Knapsack 97 97
Bin Packing 0 0
Knapsack 0 0
Integer Knapsack 0 0
Mixed Binary 562156 241418
General Linear 0 0
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)

Find solutions below. Download the archive containing all solutions from the Download page.

## Warning in lapply(df["exactobjval"], as.numeric): NAs introduced by coercion
ID Objective Exact Int. Viol Cons. Viol Obj. Viol Submitter Date Description
4 -44837.25 -44837.25 0 0 0 Michael Winkler 2022-02-25 Found with Gurobi 9.5
3 -44835.70 0 0 0 Edward Rothberg 2019-12-13 Obtained with Gurobi 9.0
2 -44827.83 0 0 0 Robert Ashford and Alkis Vazacopoulus 2019-12-18 Found using ODH|CPlex
1 -44819.68 -44819.68 0 0 0 - 2018-10-12 Solution found during MIPLIB2017 problem selection.

Similar instances in collection

The following instances are most similar to hgms62 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
hgms30 open 23797 547 0 23250 281917 850486 Jesus Rodriguez hgms -44338.3173275985* aggregations variable_bound set_partitioning set_packing set_covering invariant_knapsack equation_knapsack mixed_binary
hgms-det hard 1322 547 0 775 9752 32367 Jesus Rodriguez hgms -47314.08587415493 aggregations variable_bound set_partitioning set_packing set_covering invariant_knapsack equation_knapsack mixed_binary
neos-1122047 easy 5100 100 0 5000 57791 163640 NEOS Server Submission neos-pseudoapplication-46 161 benchmark benchmark_suitable precedence variable_bound mixed_binary
neos-5251015-ogosta hard 136971 232 0 136739 486531 1955388 Hans Mittelmann neos-pseudoapplication-19 0.1058 feasibility aggregations variable_bound set_partitioning set_packing cardinality mixed_binary
irish-electricity easy 61728 9888 0 51840 104259 523257 Paula Carroll 3723497.591396 benchmark benchmark_suitable precedence variable_bound invariant_knapsack binpacking knapsack mixed_binary

Reference

@unpublished{key ,
author = {Jesus Rodriguez, Miguel Anjos, Pascal Côté, Guy Desaulniers},
title = {Generator maintenance scheduling in hydro-power systems: MIP formulations and model selection},
note = {Manuscript in preparation},
year = {2017}
}

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