hgms-det

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	1322	9752	2.5106e-03	hard	hgms	-47314.08587415493	hgms-det.mps.gz

Maintenance scheduling of generators in hydropower systems

Location of instance in collection

Instance Statistics

Detailed explanation of the following tables can be found here.

Size Related Properties
	Original	Presolved
Variables	1322	1237
Constraints	9752	9626
Binaries	547	524
Integers	0	0
Continuous	775	713
Implicit Integers	0	0
Fixed Variables	62	0
Nonzero Density	0.00251060	0.00225709
Nonzeroes	32367	26876

Constraint Classification Properties
	Original	Presolved
Total	9752	9626
Empty	0	0
Free	0	0
Singleton	49	0
Aggregations	75	75
Precedence	0	0
Variable Bound	299	5389
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	9069	3904
General Linear	0	0
Indicator	0	0

Structure

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

Nonzero entries of original problem

Nonzero entries after trivial presolving

Decomposed structure of original problem (dec-file)

Decomposed structure after trivial presolving (dec-file)

	value	min	median	mean	max
Components	2.096910
Constraint %		0.0103993	0.471073	0.296381	1.62230
Variable %		0.1512860	0.551462	0.378215	7.41301
Score	0.580151

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
2	-47314.09		0	0	0	Robert Bixby	2020-02-10	Solved with Gurobi 9.0 within 11 hours
1	-47314.09	-47314.09	0	0	0	-	2018-10-12	Solution found during MIPLIB2017 problem selection.

Similar instances in collection

The following instances are most similar to hgms-det 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	-44338.74480308597*	aggregations variable_bound set_partitioning set_packing set_covering invariant_knapsack equation_knapsack mixed_binary
hgms62	open	48597	547	0	48050	582237	1753238	Jesus Rodriguez	hgms	-44837.24534313961*	aggregations variable_bound set_partitioning set_packing set_covering invariant_knapsack equation_knapsack mixed_binary
rocI-3-11	easy	5132	3894	762	476	8165	20540	Joerg Rambau	rocI	-50403	numerics aggregations precedence variable_bound set_partitioning mixed_binary general_linear
rocI-4-11	easy	6839	5192	1016	631	10883	27383	Joerg Rambau	rocI	-6020203	benchmark benchmark_suitable aggregations precedence variable_bound set_partitioning mixed_binary general_linear
neos-4333596-skien	easy	1005	460	0	545	812	5811	Jeff Linderoth	neos-pseudoapplication-43	-14610731.01	benchmark_suitable aggregations precedence variable_bound set_partitioning cardinality 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}
}