map10

benchmark benchmark_suitable precedence variable_bound knapsack mixed_binary

Submitter	Variables	Constraints	Density	Status	Group	Objective	MPS File
Kiyan Ahmadizadeh	164547	328818	1.01637e-05	easy	map	-495	map10.mps.gz

Land parcel selection problems motivated by Red-Cockaded Woodpecker conservation problem Imported from MIPLIB2010.

Location of instance in collection

Instance Statistics

Detailed explanation of the following tables can be found here.

Size Related Properties
	Original	Presolved
Variables	164547	26843
Constraints	328818	50120
Binaries	146	118
Integers	0	0
Continuous	164401	26725
Implicit Integers	0	0
Fixed Variables	1	0
Nonzero Density	1.01637e-05	7.93223e-05
Nonzeroes	549920	106718

Constraint Classification Properties
	Original	Presolved
Total	328818	50120
Empty	0	0
Free	0	0
Singleton	118493	0
Aggregations	0	0
Precedence	36827	21106
Variable Bound	164400	23593
Set Partitioning	0	0
Set Packing	0	0
Set Covering	0	0
Cardinality	0	0
Invariant Knapsack	0	0
Equation Knapsack	0	0
Bin Packing	0	0
Knapsack	1	1
Integer Knapsack	0	0
Mixed Binary	9097	5420
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	3.257439
Constraint %		0.0020000	0.0059800	0.0020000	0.494812
Variable %		0.0107956	0.0269732	0.0107956	1.943210
Score	0.107784

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
2	-495	-495	0	0	0	-	2018-10-13	Solution imported from MIPLIB2010.
1	-495	-495	0	0	0	-	2018-10-13	Solution found during MIPLIB2017 problem selection.

Similar instances in collection

The following instances are most similar to map10 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	Continuous	Constraints	Nonz.	Submitter	Group	Objective	Tags
map06	easy	164547	146	164401	328818	549920	Kiyan Ahmadizadeh	map	-289	benchmark_suitable precedence variable_bound knapsack mixed_binary
map16715-04	easy	164547	146	164401	328818	549920	Kiyan Ahmadizadeh	map	-111	benchmark benchmark_suitable precedence variable_bound knapsack mixed_binary
map18	easy	164547	146	164401	328818	549920	Kiyan Ahmadizadeh	map	-847	benchmark_suitable precedence variable_bound knapsack mixed_binary
map14860-20	easy	164547	146	164401	328818	549920	Kiyan Ahmadizadeh	map	-922	benchmark_suitable precedence variable_bound knapsack mixed_binary
neos-3209462-rhin	hard	56453	383	56070	170226	447473	Jeff Linderoth	neos-pseudoapplication-98	12	aggregations precedence variable_bound set_partitioning set_covering cardinality invariant_knapsack mixed_binary

Reference

@inproceedings{AhmadizadehDilkinaGomesSabharwal2010,
 author = {Ahmadizadeh, Kiyan and Dilkina, Bistra and Gomes, Carla P. and
Sabharwal, Ashish},
 booktitle = {Principles and Practice of Constraint Programming},
 pages = {514--521},
 series = {Lecture Notes in Computer Science},
 title = {An Empirical Study of Optimization for Maximizing Diffusion in
Networks},
 volume = {6308}
}

@inproceedings{SheldonETAL2010,
 author = {Sheldon, Daniel and Dilkina, Bistra and Elmachtoub, Adam and Finseth, Ryan and Sabharwal, Ashish and Conrad, Jon and Gomes, Carla P. and Shmoys, David and Allen, Will
and Amundsen, Ole and
Vaughan, Buck},
 booktitle = {Proceedings of the 26th Conference on
Uncertainty in Artificial Intelligence},
 pages = {517-526},
 title = {Maximizing Spread of Cascades Using Network Design},
 year = {2010}
}