maritime-jg3d9

infeasible decomposition aggregations precedence variable_bound set_partitioning set_packing cardinality invariant_knapsack mixed_binary general_linear

Submitter	Variables	Constraints	Density	Status	Group	Objective	MPS File
Dimitri Papageorgiou	92261	126621	5.37544e-05	easy	maritime	Infeasible	maritime-jg3d9.mps.gz

Maritime Inventory Routing Problems: Jiang-Grossmann Instances. These instances are available at https://mirplib.scl.gatech.edu/instances, along with a host of additional information such as the underlying data used to generate the model, best known upper and lower bounds, and more. They involve a single product maritime inventory routing problem and explore the use of continuous and discrete time models. A continuous-time model based on time slots for single docks is used for some instances. A model based on event points to handle parallel docks is used in others. A discrete time model based on a single commodity fixed-charge network flow problem (FCNF) is used for other instances. All the models are solved for multiple randomly generated instances of different problems to compare their computational efficiency.

Location of instance in collection

Instance Statistics

Detailed explanation of the following tables can be found here.

Size Related Properties
	Original	Presolved
Variables	92261	33368
Constraints	126621	35785
Binaries	36960	5525
Integers	0	1
Continuous	55301	27842
Implicit Integers	0	1
Fixed Variables	11	0
Nonzero Density	5.37544e-05	1.43146e-04
Nonzeroes	627969	170927

Constraint Classification Properties
	Original	Presolved
Total	126621	35785
Empty	0	0
Free	0	0
Singleton	29564	0
Aggregations	0	24141
Precedence	0	1367
Variable Bound	53784	3011
Set Partitioning	15	24
Set Packing	4152	1573
Set Covering	0	0
Cardinality	5055	1909
Invariant Knapsack	3384	1388
Equation Knapsack	0	0
Bin Packing	0	0
Knapsack	0	0
Integer Knapsack	0	0
Mixed Binary	30667	2371
General Linear	0	1
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	2.605305
Constraint %		0.002900	0.231677	0.173742	22.6009
Variable %		0.181634	0.242594	0.181634	22.5673
Score	0.879016

Best Known Solution(s)

No solution available for maritime-jg3d9 .

Similar instances in collection

The following instances are most similar to maritime-jg3d9 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
neos-5093327-huahum	easy	40640	64	40576	51840	784768	Jeff Linderoth	neos-pseudoapplication-17	6259.999997125895	benchmark decomposition benchmark_suitable aggregations mixed_binary
neos-5076235-embley	easy	49686	98	49588	63112	1089564	Jeff Linderoth	neos-pseudoapplication-17	2362	decomposition benchmark_suitable aggregations mixed_binary
neos-5079731-flyers	easy	49686	98	49588	63112	1089564	Jeff Linderoth	neos-pseudoapplication-17	2439.999999949	decomposition benchmark_suitable aggregations mixed_binary
neos-5100895-inster	easy	29400	56	29344	39760	693168	Jeff Linderoth	neos-pseudoapplication-17	3132	benchmark_suitable aggregations mixed_binary
neos-5041822-cockle	open	227668	149313	78355	546733	1362468	Jeff Linderoth	neos-pseudoapplication-25	5724245.704467608*	aggregations precedence variable_bound set_packing mixed_binary

Reference

@article{jiang2015alternative,
  title={Alternative mixed-integer linear programming models of a maritime inventory routing problem},
  author={Jiang, Yongheng and Grossmann, Ignacio E},
  journal={Computers \& Chemical Engineering},
  volume={77},
  pages={147--161},
  year={2015},
  publisher={Elsevier}
}

@article{papageorgiou2014mirplib,
  title={MIRPLib--A library of maritime inventory routing problem instances: Survey, core model, and benchmark results},
  author={Papageorgiou, Dimitri J and Nemhauser, George L and Sokol, Joel and Cheon, Myun-Seok and Keha, Ahmet B},
  journal={European Journal of Operational Research},
  volume={235},
  number={2},
  pages={350--366},
  year={2014},
  publisher={Elsevier}
}