hgms30

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 23797 281917 1.26772e-04 open hgms -44335.2204354* hgms30.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 23797 21914
Constraints 281917 279397
Binaries 547 524
Integers 0 0
Continuous 23250 21390
Implicit Integers 0 0
Fixed Variables 1860 0
Nonzero Density 0.000126772 0.000112151
Nonzeroes 850486 686670
Constraint Classification Properties
Original Presolved
Total 281917 279397
Empty 0 0
Free 0 0
Singleton 49 0
Aggregations 742 742
Precedence 0 0
Variable Bound 8854 161607
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 272012 116790
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 2.898725
Constraint % 0.000358 0.0735319 0.0093100 1.664720
Variable % 0.008400 0.0633466 0.0126066 0.777409
Score 0.578388

Best Known Solution(s)

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
1 -44335.22 -44335.22 0 0 0 - 2018-10-12 Solution found during MIPLIB2017 problem selection.

Similar instances in collection

The following instances are most similar to hgms30 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
hgms62 open 48597 547 0 48050 582237 1753240 Jesus Rodriguez hgms -44819.67625* aggregations variable_bound set_partitioning set_packing set_covering invariant_knapsack equation_knapsack mixed_binary
hgms-det open 1322 547 0 775 9752 32367 Jesus Rodriguez hgms -47314.08587416* 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 1955390 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}
}

Last Update Jun 24, 2019 by Gregor Hendel
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