nursesched-sprint-hidden09

benchmark_suitable set_partitioning set_packing cardinality invariant_knapsack general_linear

Submitter	Variables	Constraints	Density	Status	Group	Objective	MPS File
Haroldo Gambini Santos	11650	4872	3.66551e-03	easy	nursescheduling	338	nursesched-sprint-hidden09.mps.gz

Nurse Scheduling Problems from the First International Nurse Rostering Competition - INRC 2010

Location of instance in collection

Instance Statistics

Detailed explanation of the following tables can be found here.

Size Related Properties
	Original	Presolved
Variables	11650	10820
Constraints	4872	4190
Binaries	11630	10800
Integers	20	20
Continuous	0	0
Implicit Integers	0	0
Fixed Variables	0	0
Nonzero Density	0.00366551	0.00451564
Nonzeroes	208050	204720

Constraint Classification Properties
	Original	Presolved
Total	4872	4190
Empty	0	0
Free	0	0
Singleton	10	0
Aggregations	0	0
Precedence	0	0
Variable Bound	0	0
Set Partitioning	604	644
Set Packing	1410	1490
Set Covering	320	0
Cardinality	388	336
Invariant Knapsack	2040	1700
Equation Knapsack	0	0
Bin Packing	0	0
Knapsack	0	0
Integer Knapsack	0	0
Mixed Binary	80	0
General Linear	20	20
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	1.491362
Constraint %		0.1670640	2.55370	2.52983	4.96420
Variable %		0.0924214	3.32717	2.40296	7.48614
Score	0.735227

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	338	338	0	0	0	-	2018-10-12	Solution found during MIPLIB2017 problem selection.

Similar instances in collection

The following instances are most similar to nursesched-sprint-hidden09 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	Constraints	Nonz.	Submitter	Group	Objective	Tags
nursesched-medium-hint03	hard	34248	34170	78	14062	622800	Haroldo Gambini Santos	nursescheduling	115	benchmark decomposition benchmark_suitable set_partitioning set_packing cardinality invariant_knapsack general_linear
nursesched-sprint-late03	easy	11690	11670	20	5032	208410	Haroldo Gambini Santos	nursescheduling	48	decomposition benchmark_suitable set_partitioning set_packing cardinality invariant_knapsack general_linear
nursesched-sprint02	easy	10250	10230	20	3522	204000	Haroldo Gambini Santos	nursescheduling	57.99999999999999	benchmark benchmark_suitable set_partitioning set_packing cardinality invariant_knapsack general_linear
nursesched-medium04	easy	29667	29613	54	8668	621829	Haroldo Gambini Santos	nursescheduling	237	decomposition benchmark_suitable set_partitioning set_packing set_covering cardinality invariant_knapsack general_linear
academictimetablesmall	easy	28926	28926	0	23294	268350	Joshua Friedman	–	0	benchmark binary decomposition benchmark_suitable aggregations precedence variable_bound set_partitioning set_packing cardinality invariant_knapsack equation_knapsack binpacking knapsack

Reference

@Article{Santos2016,
author="Santos, Haroldo G.
and Toffolo, T{\'u}lio A. M.
and Gomes, Rafael A. M.
and Ribas, Sabir",
title="Integer programming techniques for the nurse rostering problem",
journal="Annals of Operations Research",
year="2016",
volume="239",
number="1",
pages="225--251",
issn="1572-9338",
doi="10.1007/s10479-014-1594-6",
url="http://dx.doi.org/10.1007/s10479-014-1594-6"
}