rvb-sub

binary set_partitioning knapsack

Submitter Variables Constraints Density Status Group Objective MPS File
S. Weider 33765 225 1.29542e-01 hard 16.08499802 rvb-sub.mps.gz

Set partitioning instance resulting from a column generation algorithm used for duty scheduling in public transportation Imported from MIPLIB2010.

Instance Statistics

Detailed explanation of the following tables can be found here.

Size Related Properties
Original Presolved
Variables 33765 33763
Constraints 225 225
Binaries 33763 33763
Integers 0 0
Continuous 2 0
Implicit Integers 0 0
Fixed Variables 0 0
Nonzero Density 0.129542 0.129549
Nonzeroes 984143 984141
Constraint Classification Properties
Original Presolved
Total 225 225
Empty 0 0
Free 0 0
Singleton 0 0
Aggregations 0 0
Precedence 0 0
Variable Bound 0 0
Set Partitioning 223 223
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 2
Integer Knapsack 0 0
Mixed Binary 2 0
General Linear 0 0
Indicator 0 0

Structure

Available nonzero structure and decomposition information. Further information can be found here.

value min median mean max
Components 0.301030
Constraint % 0.888889 0.888889 0.888889 0.888889
Variable % 98.631600 98.631600 98.631600 98.631600
Score 0.000122

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 Int. Viol Cons. Viol Obj. Viol Submitter Date Description
2 16.08500 0 0 0 Edward Rothberg 2020-02-05 Solved with Gurobi 9.0 within 8 hours
1 16.70222 0 0 0 - 2018-10-12 Solution found during MIPLIB2017 problem selection.

Similar instances in collection

The following instances are most similar to rvb-sub 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
ivu52 hard 157591 157591 0 0 2116 2179476 S. Weider ivu 481.0068 binary set_partitioning invariant_knapsack knapsack mixed_binary
square47 easy 95030 94987 43 0 61591 27329856 Sascha Kurz square 15.9999999997877 benchmark benchmark_suitable set_partitioning general_linear
square41 easy 62234 62197 37 0 40160 13566426 Sascha Kurz square 15 benchmark benchmark_suitable set_partitioning general_linear
eilC76-2 easy 28599 28599 0 0 75 314837 J. Linderoth eil 762.514781999996 binary benchmark_suitable set_partitioning
eilA101-2 easy 65832 65832 0 0 100 959373 J. Linderoth eil 880.9201079999999 benchmark binary benchmark_suitable set_partitioning

Reference

@inproceedings{BorndoerferLoebelWeider2008,
 author = {Ralf Bornd{\"o}rfer and Andreas L{\"o}bel and Steffen
Weider},
 booktitle = {Computer-aided Systems in Public Transport},
 editor = {Mark Hickman and Pitu Mirchandani and Stefan Voß},
 pages = {3--24},
 series = {Lecture Notes in Economics and Mathematical Systems},
 title = {A Bundle Method for Integrated Multi-Depot Vehicle and
Duty Scheduling in Public Transit},
 volume = {600},
 year = {2008}
}

@phdthesis{Weider2007,
 author = {Steffen Weider},
 school = {Technische Universit{\"a}t Berlin},
 title = {Integration of Vehicle and Duty Scheduling in Public
Transport},
 year = {2007}
}

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