ivu52

binary set_partitioning invariant_knapsack knapsack mixed_binary

Submitter Variables Constraints Density Status Group Objective MPS File
S. Weider 157591 2116 6.53589e-03 hard ivu 481.0068 ivu52.mps.gz

Set partitioning instance resulting from a column generation algorithm used for duty scheduling in public transportation. Solved in June 2014 using CPLEX 12.6 with 48 threads in about 25 days. Imported from MIPLIB2010.

Instance Statistics

Detailed explanation of the following tables can be found here.

Size Related Properties
Original Presolved
Variables 157591 157591
Constraints 2116 2116
Binaries 157591 157591
Integers 0 0
Continuous 0 0
Implicit Integers 0 0
Fixed Variables 0 0
Nonzero Density 0.00653589 0.00653589
Nonzeroes 2179480 2179480
Constraint Classification Properties
Original Presolved
Total 2116 2116
Empty 0 0
Free 0 0
Singleton 0 0
Aggregations 0 0
Precedence 0 0
Variable Bound 0 0
Set Partitioning 2110 2110
Set Packing 0 0
Set Covering 0 0
Cardinality 0 0
Invariant Knapsack 1 1
Equation Knapsack 0 0
Bin Packing 0 0
Knapsack 1 3
Integer Knapsack 0 0
Mixed Binary 4 2
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 % 0.047259 0.047259 0.047259 0.047259
Variable % 0.324257 0.324257 0.324257 0.324257
Score 0.000471

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
1 481.3141 2e-07 2e-07 0 - 2018-10-12 Solution found during MIPLIB2017 problem selection.

Similar instances in collection

The following instances are most similar to ivu52 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
square37 easy 49320 49284 36 0 33150 9475672 Sascha Kurz square 14.9999997973 benchmark_suitable set_partitioning general_linear
square31 easy 28860 28830 30 0 19435 3937200 Sascha Kurz square 15 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
rvb-sub hard 33765 33763 0 2 225 984143 S. Weider 16.08499802 binary set_partitioning knapsack
square23 easy 11660 11638 22 0 7887 898813 Sascha Kurz square 13 benchmark_suitable set_partitioning general_linear

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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