Difference between revisions of "MacMINLP"

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This page contains a collection of '''Mixed Integer Nonlinear Programming (MINLP)''' test problems in [http://www.ampl.com/ AMPL]. A [http://netlib.bell-labs.com/netlib/ampl/student/index.html student version of AMPL] is available for free which can handle problems with up to 300 variables or constraints.
 
This page contains a collection of '''Mixed Integer Nonlinear Programming (MINLP)''' test problems in [http://www.ampl.com/ AMPL]. A [http://netlib.bell-labs.com/netlib/ampl/student/index.html student version of AMPL] is available for free which can handle problems with up to 300 variables or constraints.
  
The integer variables, Special Ordered Sets and priorities are specified through an [http://www.mcs.anl.gov/~leyffer/MacMINLP/problems/int_format int file]. Note that the int file is not required by default as AMPL allows the definition of integer variables.
+
The integer variables, Special Ordered Sets and priorities are specified through an [http://www.mcs.anl.gov/~leyffer/MacMINLP/int_format int file]. Note that the int file is not required by default as AMPL allows the definition of integer variables.
  
 
In the Table below, the following column headings are used:
 
In the Table below, the following column headings are used:

Revision as of 13:26, 27 July 2012

This page contains a collection of Mixed Integer Nonlinear Programming (MINLP) test problems in AMPL. A student version of AMPL is available for free which can handle problems with up to 300 variables or constraints.

The integer variables, Special Ordered Sets and priorities are specified through an int file. Note that the int file is not required by default as AMPL allows the definition of integer variables.

In the Table below, the following column headings are used:

heading meaning
NAME the name of the problem, click for a short reference
mod file the corresponding ampl model file
dat file the corresponding ampl data file
int file the corresponding [int_format integer file]
CUTE classification Classification as Nonlinear Program (NLP)
#int the number of integer variables
convex (Y/N) depending on whether the problem is convex or not; (Y*=pseudo-convex)
f(x) objective value of NLP relaxation
f(x*) optimal objective value or best solution found

The collection is available as a single [MacMINLP.tar.gz tar file] (simply gunzip and tar xf the file) or as individual problems below or as a [MacMINLP.nl.tar.gz collection of stub.nl files] which can be interpreted by an AMPL solver interface and do not require the AMPL itself. A file with the MINLP AMPL commands used to run the problems is also available.

Click on the NAME of the problem for a short description. The complete list of descriptions can be found in the MINLP Comments. Finally, a list of updates and changes to the AMPL files and the int files is MINLP Updates.

NAME mod file dat file int file CUTE classification #int convex f(x) f(x*)
batch

batch.mod

n/a

batch.int

OOR2-AN-46-73 24 Y 259180 285507
c-reload-14a

c-reload.mod

c-reload-14a.dat

c-reload.int

OOR2-AN-342-308 168 N -1.00752 -1.00743
c-reload-14b

c-reload.mod

c-reload-14b.dat

c-reload.int

LOR2-AN-342-308 168 N -1.0253 -1.02522
c-reload-14c

c-reload.mod

c-reload-14c.dat

c-reload.int

LOR2-AN-342-308 168 N -0.99595 -0.99988
c-reload-14d

c-reload.mod

c-reload-14d.dat

c-reload.int

LOR2-AN-342-308 168 N -1.0340 -1.03405
c-reload-14e

c-reload.mod

c-reload-14e.dat

c-reload.int

LOR2-AN-342-308 168 N -1.0326 -1.03306
c-reload-14f

c-reload.mod

c-reload-14f.dat

c-reload.int

LOR2-AN-342-308 168 N -1.0172 -1.01784
c-reload-q-24

c-reload-q.mod

c-reload-q-24.dat

n/a LOR2-AN-968-632 576 N -1.12795 -1.12795
c-reload-q-25

c-reload-q.mod

c-reload-q-25.dat

n/a LOR2-AN-1033-658 625 N ? ?
c-reload-q-49

c-reload-q.mod

c-reload-q-49.dat

n/a LOR2-AN-3292-1430 2401 N ? ?
c-reload-q-104

c-reload-q.mod

c-reload-q-104.dat

n/a LOR2-AN-12906-3338 10816 N ? ?
c-sched1

c-sched.mod

c-sched1.dat

c-sched1.int

OLR2-AN-73-16 60 Y* -30640.6 -30639.3
c-sched2

c-sched.mod

c-sched2.dat

c-sched2.int

OLR2-AN-400-137 308 Y* -166247 -166102
feedloc

feedloc.mod

n/a

feedloc.int

LOR2-AN-90-259 37 N 0.0 0.0
geartrain

geartrain.mod

n/a n/a OBR2-AN-4-0 4 Y 9.23355E-11 7.77863E-07
lbti-00-15

lbti-00.mod

lbti-00-15.dat

n/a OOR2-AN-274-402 169 N ? 0.988
lbti-00-20

lbti-00.mod

lbti-00-20.dat

n/a OOR2-AN-274-402 169 N ? 0.988
lbti-00-40

lbti-00.mod

lbti-00-40.dat

n/a OOR2-AN-274-402 169 N ? 0.988
lbti-01-15

lbti-01.mod

lbti-01-15.dat

n/a OOR2-AN-334-502 229 N ? 0.983
lbti-01-20

lbti-01.mod

lbti-01-20.dat

n/a OOR2-AN-334-502 229 N ? 0.983
lbti-01-40

lbti-01.mod

lbti-01-40.dat

n/a OOR2-AN-334-502 229 N ? 0.983
lbti-02-297

lbti-02.mod

lbti-02-297.dat

n/a QOR2-AN-7101-13004 6702 N ? 1.21
mittelman

mittelman.mod

n/a n/a OOR2-AN-16-7 16 N 5.02361 13.0000
optprloc

optprloc.mod

n/a n/a QQR2-AN-30-29 25 Y -16.4198 -8.06414
space-25

space-25.mod

space-25.dat

space-25.int

LQR2-AN-893-235 750 N 483.811 484.329
space-25-r

space-25-r.mod

space-25-r.dat

space-25.int

LQR2-AN-818-160 750 N 483.811 484.329
space-960

space-960.mod

space-960.dat

space-960.int

LQR2-AN-15137-8417 9600 N ? ?
space-960-i

space-960-i.mod

space-960-i.dat

n/a LQR2-AN-5537-6497 960 N ? ?
space-960-ir

space-960-ir.mod

space-960-ir.dat

n/a LQR2-AN-2657-3617 960 N ? ?
space-960-r

space-960-r.mod

space-960-r.dat

space-960.int

LQR2-AN-12257-5537 9600 N ? ?
spring

spring.mod

n/a

spring.int

OOR2-AN-17-10 11 N 0.832025 0.846246
stockcycle

stockcycle.mod

n/a

stockcycle.int

OLR2-AN-480-97 480 Y 117916 121113 ?
synthes1

synthes1.mod

n/a n/a OOR2-AN-6-6 3 Y 0.759284 6.00976
synthes2

synthes2.mod

n/a n/a OOR2-AN-11-14 5 Y -0.554417 73.0353
synthes3

synthes3.mod

n/a n/a OOR2-AN-17-19 8 Y 15.0822 68.0097
top1-15x05

top.mod

top1-15x05.dat

top.scl

OQR2-MN-260-186 75 N 203.343 NLP fail
top1-30x10

top.mod

top1-30x10.dat

top.scl

OQR2-MN-970-671 300 N 202.92 ?
top1-60x20

top.mod

top1-60x20.dat

top.scl

OQR2-MN-3740-2541 1200 N ? ?
trimlon2

trimlon.mod

trimlon2.dat

trimlon.int

LOR2-AN-8-12 8 N 4.06375 5.3
trimlon4

trimlon.mod

trimlon4.dat

trimlon.int

LOR2-MN-24-26 24 N 7.66333 11.3
trimlon5

trimlon.mod

trimlon5.dat

trimlon.int

LOR2-MN-35-33 35 N 9.664 12.1
trimlon6

trimlon.mod

trimlon6.dat

trimlon.int

LOR2-MN-48-41 48 N 14.6913 19.4
trimlon7

trimlon.mod

trimlon7.dat

trimlon.int

LOR2-MN-63-42 63 N 13.6507 ?
trimlon12

trimlon.mod

trimlon12.dat

trimlon.int

LOR2-MN-168-72 168 N 85.3546 ?
trimloss2

trimloss.mod

trimloss2.dat

trimloss2.int

LOR2-AN-37-24 31 Y 0.718306 5.3
trimloss4

trimloss.mod

trimloss4.dat

trimloss4.int

LOR2-MN-105-64 85 Y 1.70933 9.3
trimloss5

trimloss.mod

trimloss5.dat

trimloss5.int

LOR2-MN-161-90 131 Y 1.1788683 10.3
trimloss6

trimloss.mod

trimloss6.dat

trimloss6.int

LOR2-MN-215-120 173 Y 1.30565 ?
trimloss7

trimloss.mod

trimloss7.dat

trimloss7.int

LOR2-MN-345-154 289 Y 0.593496 ?
trimloss12

trimloss.mod

trimloss12.dat

trimloss12.int

LOR2-MN-800-372 656 Y 2.31187 ?
wind-fac

wind-fac.mod

n/a n/a LOR2-AN-15-14 3 N 0.118262 0.254487
MacMINLP: ampl collection of MINLP Test Problems