gfd-schedulen180f7d50m30k18

benchmark feasibility benchmark_suitable aggregations precedence variable_bound set_partitioning cardinality invariant_knapsack mixed_binary general_linear

Submitter	Variables	Constraints	Density	Status	Group	Objective	MPS File
Gleb Belov	227535	457985	1.18357e-05	easy	gfd-schedule	1	gfd-schedulen180f7d50m30k18.mps.gz

Linearized Constraint Programming models of the MiniZinc Challenges 2012-2016. I should be able to produce versions with indicator constraints supported by Gurobi and CPLEX, however don’t know if you can use them and if there is a standard format. These MPS were produced by Gurobi 7.0.2 using the MiniZinc develop branch on eb536656062ca13325a96b5d0881742c7d0e3c38. Solved with COPT 7.0 using up to 12 threads in less than 30 minutes.

Location of instance in collection

Instance Statistics

Detailed explanation of the following tables can be found here.

Size Related Properties
	Original	Presolved
Variables	227535	149415
Constraints	457985	297065
Binaries	192408	145675
Integers	2025	1987
Continuous	33102	1753
Implicit Integers	0	162
Fixed Variables	31552	0
Nonzero Density	1.18357e-05	1.85317e-05
Nonzeroes	1233370	822546

Constraint Classification Properties
	Original	Presolved
Total	457985	297065
Empty	0	0
Free	0	0
Singleton	38	0
Aggregations	41507	10157
Precedence	102946	66488
Variable Bound	43777	38276
Set Partitioning	447	1200
Set Packing	0	0
Set Covering	0	0
Cardinality	33060	32277
Invariant Knapsack	16624	16563
Equation Knapsack	0	0
Bin Packing	0	0
Knapsack	0	0
Integer Knapsack	0	0
Mixed Binary	66958	4066
General Linear	152628	128038
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
Constraint %
Variable %
Score

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

Similar instances in collection

The following instances are most similar to gfd-schedulen180f7d50m30k18 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
oocsp-racks030e6cci	easy	50862	32783	18079	0	92737	232944	Gleb Belov	oocsp-racks	0	feasibility indicator numerics aggregations precedence variable_bound set_partitioning set_covering cardinality invariant_knapsack integer_knapsack general_linear
cryptanalysiskb128n5obj16	easy	48950	47830	1120	0	98021	292875	Gleb Belov	cryptanalysis	0	benchmark feasibility benchmark_suitable aggregations precedence variable_bound set_covering cardinality invariant_knapsack binpacking knapsack integer_knapsack mixed_binary general_linear
cryptanalysiskb128n5obj14	hard	48950	47830	1120	0	98021	292875	Gleb Belov	cryptanalysis	Infeasible	benchmark infeasible feasibility benchmark_suitable aggregations precedence variable_bound set_covering cardinality invariant_knapsack binpacking knapsack integer_knapsack mixed_binary general_linear
oocsp-racks030f7cci	easy	50859	32779	18080	0	92792	233170	Gleb Belov	oocsp-racks	Infeasible	infeasible feasibility indicator numerics aggregations precedence variable_bound set_partitioning set_covering cardinality invariant_knapsack integer_knapsack general_linear
l2p12	easy	11786	10906	590	290	21315	59629	Gleb Belov	l2p	5	benchmark_suitable aggregations precedence variable_bound set_partitioning set_packing cardinality invariant_knapsack general_linear

Reference

@Inbook{Belov2016,
author="Belov, Gleb
and Stuckey, Peter J.
and Tack, Guido
and Wallace, Mark",
editor="Rueher, Michel",
title="Improved Linearization of Constraint Programming Models",
bookTitle="Principles and Practice of Constraint Programming: 22nd International Conference, CP 2016, Toulouse, France, September 5-9, 2016, Proceedings",
year="2016",
publisher="Springer International Publishing",
pages="49--65",
isbn="978-3-319-44953-1",
doi="10.1007/978-3-319-44953-1_4",
url="http://dx.doi.org/10.1007/978-3-319-44953-1_4"
}