zeil

precedence variable_bound mixed_binary

Submitter	Variables	Constraints	Density	Status	Group	Objective	MPS File
Andreas Bärmann	70116	81558	2.84854e-04	open	–	1086.261999999988*	zeil.mps.gz

A model that computes an optimal adaptation of a given timetable draft for a small portion of the German railway network. The aim is to shift the planned departure times of the trains slightly, such that the maximum power consumption (averaed over 15-minute intervalls of the planning horizon) is as small as possible.

Location of instance in collection

Instance Statistics

Detailed explanation of the following tables can be found here.

Size Related Properties
	Original	Presolved
Variables	70116	66940
Constraints	81558	71271
Binaries	5314	4551
Integers	0	0
Continuous	64802	62389
Implicit Integers	0	0
Fixed Variables	0	0
Nonzero Density	0.000284854	0.000295156
Nonzeroes	1628940	1408150

Constraint Classification Properties
	Original	Presolved
Total	81558	71271
Empty	0	0
Free	0	0
Singleton	2928	0
Aggregations	0	0
Precedence	15922	8813
Variable Bound	120	85
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	0	0
Integer Knapsack	0	0
Mixed Binary	62588	62373
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	0.602060
Constraint %		0.0238526	4.16158	0.297456	12.16340
Variable %		0.0177245	2.28252	0.187584	6.64225
Score	0.116763

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	Submitter	Date	Description
5	1086.262	1086.262	Ed Rothberg	2023-05-19	Found with the NoRel heuristic.
4	1109.554	1109.554	Edward Rothberg	2020-06-11	Obtained with Gurobi 9.0 using the solution improvement heuristic
3	1169.939		Edward Rothberg	2019-12-13	Obtained with Gurobi 9.0
2	1229.677		Robert Ashford and Alkis Vazacopoulus	2019-12-18	Found using ODH\|CPlex
1	1330.041	1330.041	-	2018-10-12	Solution found during MIPLIB2017 problem selection.

Similar instances in collection

The following instances are most similar to zeil 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
neos-1420546	open	26055	1125	0	24930	12671	67959	NEOS Server Submission	neos-pseudoapplication-9	22948.10433777*	decomposition set_partitioning mixed_binary
neos-1420790	open	4926	540	0	4386	2310	12720	NEOS Server Submission	neos-pseudoapplication-9	3119.806001594*	decomposition set_partitioning mixed_binary
germany50-UUM	hard	6971	0	88	6883	2088	20737	MIPLIB submission pool	network_design	628490	decomposition aggregations mixed_binary general_linear
uccase10	open	110818	16800	0	94018	196498	787045	Daniel Espinoza	uccase	39134.295915*	aggregations precedence variable_bound mixed_binary
loopha13	easy	19356	18150	0	1206	23758	41809	Hamideh	–	6.40233	benchmark_suitable aggregations precedence variable_bound invariant_knapsack mixed_binary

Reference

No bibliographic information available