pb-fit2d

binary decomposition benchmark_suitable equation_knapsack binpacking knapsack

Submitter Variables Constraints Density Status Group Objective MPS File
Gleb Belov 118500 10525 1.26328e-03 easy pb- -20425 pb-fit2d.mps.gz

These are the instances from MiniZinc Challenges 2012-2016 (see www.minizinc.org), compiled for MIP WITH INDICATOR CONSTRAINTS using the develop branch of MiniZinc and CPLEX 12.7.1 on 30 April 2017. Thus, these instances can only be handled by solvers accepting indicator constraints. For instances compiled with big-M/domain decomposition only, see my previous submission to MIPLIB. To recompile, create a directory MODELS, a list lst12_16.txt of the instances with full paths to mzn/dzn files of each instance per line, and say $> ~/install/libmzn/tests/benchmarking/mzn-test.py -l ../lst12_16.txt –slvPrf MZN-CPLEX –debug 1 –addOption “–timeout 3 -D fIndConstr=true -D fMIPdomains=false” –useJoinedName “–writeModel MODELS_IND/%s.mps” Alternatively, you can compile individual instance as follows: $> mzn-cplex -v -s -G linear –output-time ../challenge_2012_2016/mznc2016_probs/zephyrus/zephyrus.mzn ../challenge_2012_2016/mznc2016_p/zephyrus/14__8__6__3.dzn -a –timeout 3 -D fIndConstr=true -D fMIPdomains=false –writeModel MODELS_IND/challenge_2012_2016mznc2016_probszephyruszephyrusmzn-challenge_2012_2016mznc2016_probszephyrus14__8__6__3dzn.mps Imported from the MIPLIB2010 submissions.

Instance Statistics

Detailed explanation of the following tables can be found here.

Size Related Properties
Original Presolved
Variables 118500 118500
Constraints 10525 10525
Binaries 118500 118500
Integers 0 0
Continuous 0 0
Implicit Integers 0 0
Fixed Variables 0 0
Nonzero Density 0.00126328 0.00126328
Nonzeroes 1575580 1575580
Constraint Classification Properties
Original Presolved
Total 10525 10525
Empty 0 0
Free 0 0
Singleton 0 0
Aggregations 0 0
Precedence 0 0
Variable Bound 0 0
Set Partitioning 0 0
Set Packing 0 0
Set Covering 0 0
Cardinality 0 0
Invariant Knapsack 0 0
Equation Knapsack 1 1
Bin Packing 0 10500
Knapsack 0 24
Integer Knapsack 0 0
Mixed Binary 10524 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 4.021231
Constraint % 0.00950 0.00950 0.00950 0.0095000
Variable % 0.00844 0.00952 0.00928 0.0118143
Score 0.997530

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
1 -20425 -20425 0 0 0 - 2018-10-11 Solution found during MIPLIB2017 problem selection.

Similar instances in collection

The following instances are most similar to pb-fit2d 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-787933 easy 236376 236376 0 0 1897 298320 NEOS Server Submission neos-pseudoapplication-36 30 benchmark binary decomposition benchmark_suitable binpacking mixed_binary
co-100 easy 48417 48417 0 0 2187 1995817 Axel Werner 2639942.06 benchmark binary benchmark_suitable precedence set_partitioning set_packing binpacking knapsack
neos-2328163-agri easy 2236 2236 0 0 1963 12740 Jeff Linderoth neos-pseudoapplication-36 27674 binary decomposition benchmark_suitable set_partitioning set_packing set_covering cardinality invariant_knapsack binpacking knapsack
peg-solitaire-a3 easy 4552 4552 0 0 4587 28387 Hiroshige Dan ; Koichi Fujii pegsolitaire 1 benchmark binary benchmark_suitable aggregations variable_bound set_partitioning cardinality binpacking
neos-4355351-swalm open 21065 10530 0 10535 21609 371467 Jeff Linderoth neos-pseudoapplication-58 33.45757454008309* variable_bound binpacking mixed_binary

Reference

No bibliographic information available

Last Update 2024 by Julian Manns
generated with R Markdown
© by Zuse Institute Berlin (ZIB)
Imprint