Solver Square Comparison

Solver Square Comparison: Considers all models.

Results created on 03/04/11 12:14:19 using the PAVER Server/Performance tools available at http://www.gamsworld.eu/performance/paver

Compares all solver return outcomes (for example optimal, locally optimal, infeasible, unbounded, fail) of one solver with all return outcomes of another solver. Interrupt denotes resource or iteration limit has been reached.

Solver SNOPT is represented on the left (rows) and solver PATHNLP on top (columns).

See the solver return definitions for return codes. Models having trace data only in one trace file are listed in the "no data" column of the other.

Input File Number	Filename
Tracefile 1:	SNOPT-1.trc
Tracefile 2:	PATHNLP-1.trc
Solvers used :	SNOPT
	PATHNLP
Modeltype(s)	`NLP`

	PATHNLP: optimal	PATHNLP: locally optimal	PATHNLP: feasible	PATHNLP: infeasible	PATHNLP: unbounded	PATHNLP: fail	PATHNLP: no data	total SNOPT
SNOPT: optimal	-	-	-	-	-	-	-	`-`
SNOPT: locally optimal	-	`49`	`11`	-	-	`10`	-	`70`
SNOPT: feasible	-	`3`	-	-	-	`2`	-	`5`
SNOPT: infeasible	-	`1`	-	-	-	`2`	-	`3`
SNOPT: unbounded	-	-	-	-	-	-	-	`-`
SNOPT: fail	-	`1`	`2`	-	-	-	-	`3`
SNOPT: no data	-	-	-	-	-	-	-	`-`
total PATHNLP	`-`	`54`	`13`	`-`	`-`	`14`	`-`	`81`

Solver return definitions:

Outcome	Model Status	Solver Status
optimal	1 or 15	1
locally optimal	2	any
feasible	7 or 16 or 17	1 or 2 or 3 or 4 or 5
infeasible	4 or 5 or 19	1
unbounded	3 or 18	1
fail	all other	all other

Solver Resource Times

Models for each solver pair outcome. Listed are the solver resource times TIME(.) in seconds, as well as the ratio RATIO(./.) of resource times for the two solvers if both solved optimally.
Also listed are the objective values OBJ(.) using both solvers. The better solution found is listed in boldface. A solution is considered better, if the relative objective function difference is greater than 1.00E-05. If both solutions are less than 1e-1, we use the absolute difference.
Solver resource time ratios for a particular model are listed only if one solver has resource greater than 5.00E-02.

SNOPT: locally optimal -- PATHNLP: locally optimal

Modelname	Time (SNOPT)	Time (PATHNLP)	Ratio (SNOPT/PATHNLP)	Obj (SNOPT)	Obj (PATHNLP)
`arki0002`	`155.9220`	`0.7480`	`208.452`	`1.09249984`	`1.87252775`
`arki0020`	`25.4230`	`0.3860`	`65.863`	`-41.07495436`	`-41.07495436`
`arki0021`	`75.6490`	`3.5850`	`21.102`	`-72.58210091`	`-72.58210091`
`arki0022`	`103.7290`	`8.1890`	`12.667`	`-87.09909127`	`-87.09909127`
`catmix100`	`0.1660`	`0.2760`	`0.601`	`-0.04806940`	`-0.04806942`
`catmix200`	`0.6780`	`0.2730`	`2.484`	`-0.04805914`	`-0.04805914`
`catmix400`	`2.5770`	`1.8930`	`1.361`	`-0.04805655`	`-0.04805655`
`catmix800`	`10.9170`	`26.6930`	`0.409`	`-0.04805590`	`-0.04805590`
`chain400`	`7.1580`	`3.3930`	`2.110`	`5.06862169`	`5.06862169`
`ex8_2_3a`	`64.3650`	`296.1640`	`0.217`	`-3731.07808948`	`-3731.07929210`
`flowchan100`	`0.3330`	`0.1090`	`3.055`	`0.00000000`	`0.00000000`
`flowchan200`	`1.0650`	`0.2300`	`4.630`	`0.00000000`	`0.00000000`
`flowchan400`	`3.3790`	`0.4790`	`7.054`	`0.00000000`	`0.00000000`
`gasoil100`	`0.4980`	`0.2320`	`2.147`	`0.00523659`	`0.00523659`
`gasoil200`	`1.4750`	`0.7090`	`2.080`	`0.00523660`	`0.00523660`
`gasoil400`	`7.0000`	`2.2940`	`3.051`	`0.00523660`	`0.00523660`
`gasoil50`	`0.2010`	`0.1050`	`1.914`	`0.00523664`	`0.00523664`
`jbearing100`	`40.0780`	`0.5180`	`77.371`	`-0.15504196`	`-0.15504196`
`jbearing25`	`7.0120`	`0.1080`	`64.926`	`-0.15401554`	`-0.15401554`
`jbearing50`	`30.7210`	`0.3060`	`100.395`	`-0.15482422`	`-0.15482422`
`jbearing75`	`24.6340`	`0.3760`	`65.516`	`-0.15498453`	`-0.15498453`
`lnts100`	`0.3100`	`1.5830`	`0.196`	`0.55459540`	`0.55459540`
`lnts200`	`1.4820`	`43.2490`	`0.034`	`0.55457702`	`0.55457702`
`methanol100`	`0.8190`	`0.3380`	`2.423`	`0.00902229`	`0.00902229`
`methanol200`	`2.5090`	`0.9810`	`2.558`	`0.00902229`	`0.00902229`
`methanol400`	`8.4200`	`3.4380`	`2.449`	`0.00902229`	`0.00902229`
`methanol50`	`1.2120`	`0.1280`	`9.469`	`0.00902229`	`0.00902229`
`minsurf100`	`307.3960`	`0.6670`	`460.864`	`2.50694926`	`2.50694926`
`minsurf25`	`5.7500`	`0.0920`	`62.500`	`2.51948768`	`2.51948768`
`minsurf50`	`67.6010`	`0.2570`	`263.039`	`2.51488916`	`2.51488916`
`minsurf75`	`155.1750`	`0.3910`	`396.867`	`2.50568648`	`2.50568648`
`pinene100`	`2.3520`	`3.6530`	`0.644`	`19.87217014`	`19.87217015`
`pinene200`	`10.7530`	`7.7290`	`1.391`	`19.87216684`	`19.87216684`
`pinene25`	`1.1890`	`0.4780`	`2.487`	`19.87216552`	`19.87216552`
`pinene50`	`1.0510`	`0.4680`	`2.246`	`19.87216552`	`19.87216552`
`polygon25`	`0.0360`	`0.6940`	`0.052`	`-0.77973670`	`-0.77967824`
`polygon75`	`5.3170`	`14.0400`	`0.379`	`-0.78478846`	`-0.75626662`
`popdynm100`	`1.9540`	`2.0630`	`0.947`	`19746.52860217`	`19746.52860217`
`popdynm200`	`6.1400`	`6.5270`	`0.941`	`19746.52964660`	`19746.52964660`
`popdynm25`	`0.3130`	`0.1100`	`2.845`	`19752.21541511`	`19752.21541511`
`popdynm50`	`1.0690`	`0.5020`	`2.129`	`19746.54515628`	`19746.54515628`
`robot100`	`0.8920`	`0.9820`	`0.908`	`9.14268538`	`9.14268538`
`robot200`	`7.1720`	`59.6580`	`0.120`	`9.14139550`	`9.14139550`
`robot400`	`73.1190`	`52.1010`	`1.403`	`9.14102603`	`9.14102603`
`robot50`	`0.1410`	`1.0190`	`0.138`	`9.14687850`	`9.14687850`
`torsion100`	`19.8940`	`0.7090`	`28.059`	`-0.41823921`	`-0.41823921`
`torsion25`	`1.5050`	`0.0970`	`15.515`	`-0.41751073`	`-0.41751073`
`torsion50`	`14.2930`	`0.2700`	`52.937`	`-0.41808763`	`-0.41808763`
`torsion75`	`12.4500`	`0.4540`	`27.423`	`-0.41819940`	`-0.41819940`

SNOPT: locally optimal -- PATHNLP: feasible

Modelname	Time (SNOPT)	Time (PATHNLP)	Ratio (SNOPT/PATHNLP)	Obj (SNOPT)	Obj (PATHNLP)
`arki0004`	`0.4440`	`952.6750`	`0.000`	`323.46703883`	`17730.41368439`
`arki0011`	`417.8620`	`3602.5150`	`0.116`	`-224086.46000828`	`-224086.46003899`
`arki0015`	`3.7150`	`252.1530`	`0.015`	`-272.29977820`	`-180.93272868`
`camshape400`	`0.0960`	`11.0170`	`0.009`	`-4.27568692`	`-4.16698341`
`elec200`	`11.0000`	`429.8600`	`0.026`	`18438.99267601`	`22750.58850376`
`ex8_2_2a`	`118.9230`	`1205.4070`	`0.099`	`-552.66024730`	`-197.22299669`
`ex8_2_2b`	`6.6280`	`443.2060`	`0.015`	`-551.76977066`	`133.26074773`
`ex8_2_5a`	`183.9390`	`280.6110`	`0.655`	`-830.33802819`	`-454.77337863`
`ex8_2_5b`	`6.7640`	`494.0380`	`0.014`	`-830.07940808`	`-212.13223964`
`polygon100`	`21.3800`	`548.4390`	`0.039`	`-0.78503127`	`0.00000000`
`polygon50`	`1.6020`	`64.0450`	`0.025`	`-0.78401305`	`-0.65531628`

SNOPT: locally optimal -- PATHNLP: fail

Modelname	Time (SNOPT)	Time (PATHNLP)	Ratio (SNOPT/PATHNLP)	Obj (SNOPT)	Status (PATHNLP)
`arki0012`	`3241.7210`	`0.0000`	---	`-224252.44559875`	`mstat(14)sstat( 9)`
`arki0013`	`1487.5470`	`0.0000`	---	`-224253.08921843`	`mstat(14)sstat( 9)`
`camshape800`	`0.4180`	`50.6430`	---	`-4.27427301`	`mstat( 6)sstat( 4)`
`ex8_2_3b`	`22.1670`	`NA`	---	`-3730.72924771`	`mstat(13)sstat(13)`
`glider100`	`1618.6330`	`NA`	---	`-1255.05860055`	`mstat(13)sstat(13)`
`glider50`	`76.3770`	`48.7000`	---	`-1286.97737315`	`mstat( 6)sstat( 4)`
`lnts400`	`6.4850`	`289.8090`	---	`0.55457241`	`mstat( 6)sstat( 4)`
`rocket100`	`0.7420`	`52.5200`	---	`-1.01283202`	`mstat( 6)sstat( 4)`
`rocket200`	`4.6100`	`137.1480`	---	`-1.01283569`	`mstat( 6)sstat( 4)`
`rocket400`	`40.4500`	`983.9650`	---	`-1.01283661`	`mstat( 6)sstat( 4)`

SNOPT: feasible -- PATHNLP: locally optimal

Modelname	Time (SNOPT)	Time (PATHNLP)	Ratio (SNOPT/PATHNLP)	Obj (SNOPT)	Obj (PATHNLP)
`arki0017`	`1715.7910`	`4.6620`	`368.038`	`-121.83308010`	`-121.83308010`
`arki0018`	`42.2100`	`1.9770`	`21.351`	`0.01198069`	`0.01045662`
`arki0023`	`82.4830`	`47.7820`	`1.726`	`-153.41732339`	`-153.66007775`

SNOPT: feasible -- PATHNLP: fail

Modelname	Time (SNOPT)	Time (PATHNLP)	Ratio (SNOPT/PATHNLP)	Obj (SNOPT)	Status (PATHNLP)
`arki0014`	`3600.0370`	`0.0000`	---	`-223972.99474775`	`mstat(14)sstat( 9)`
`glider400`	`3599.9900`	`2768.1960`	---	`-252.52559804`	`mstat( 6)sstat( 4)`

SNOPT: infeasible -- PATHNLP: locally optimal

Modelname	Time (SNOPT)	Time (PATHNLP)	Ratio (SNOPT/PATHNLP)	Status (SNOPT)	Obj (PATHNLP)
`infeas1`	`0.0160`	`1.6080`	---	`mstat( 4)sstat( 1)`	`13685.59646388`

SNOPT: infeasible -- PATHNLP: fail

Modelname	Time (SNOPT)	Time (PATHNLP)	Ratio (SNOPT/PATHNLP)	Status (SNOPT)	Status (PATHNLP)
`arki0008`	`8.9820`	`596.2570`	---	`mstat( 5)sstat( 1)`	`mstat( 6)sstat( 4)`
`glider200`	`1.8010`	`406.4660`	---	`mstat( 5)sstat( 1)`	`mstat( 6)sstat( 4)`

SNOPT: fail -- PATHNLP: locally optimal

Modelname	Time (SNOPT)	Time (PATHNLP)	Ratio (SNOPT/PATHNLP)	Status (SNOPT)	Obj (PATHNLP)
`arki0016`	`NA`	`2.2560`	---	`mstat(13)sstat(13)`	`867.97316601`

SNOPT: fail -- PATHNLP: feasible

Modelname	Time (SNOPT)	Time (PATHNLP)	Ratio (SNOPT/PATHNLP)	Status (SNOPT)	Obj (PATHNLP)
`arki0003`	`1.1860`	`436.3120`	---	`mstat( 6)sstat( 4)`	`624676.20567527`
`ex8_2_2`	`82.6420`	`3952.3240`	---	`mstat( 6)sstat( 4)`	`25.74674493`

SNOPT: locally optimal:

Modelname	Time (SNOPT)	Obj (SNOPT)
`arki0002`	`155.9220`	`1.09249984`
`arki0004`	`0.4440`	`323.46703883`
`arki0011`	`417.8620`	`-224086.46000828`
`arki0012`	`3241.7210`	`-224252.44559875`
`arki0013`	`1487.5470`	`-224253.08921843`
`arki0015`	`3.7150`	`-272.29977820`
`arki0020`	`25.4230`	`-41.07495436`
`arki0021`	`75.6490`	`-72.58210091`
`arki0022`	`103.7290`	`-87.09909127`
`camshape400`	`0.0960`	`-4.27568692`
`camshape800`	`0.4180`	`-4.27427301`
`catmix100`	`0.1660`	`-0.04806940`
`catmix200`	`0.6780`	`-0.04805914`
`catmix400`	`2.5770`	`-0.04805655`
`catmix800`	`10.9170`	`-0.04805590`
`chain400`	`7.1580`	`5.06862169`
`elec200`	`11.0000`	`18438.99267601`
`ex8_2_2a`	`118.9230`	`-552.66024730`
`ex8_2_2b`	`6.6280`	`-551.76977066`
`ex8_2_3a`	`64.3650`	`-3731.07808948`
`ex8_2_3b`	`22.1670`	`-3730.72924771`
`ex8_2_5a`	`183.9390`	`-830.33802819`
`ex8_2_5b`	`6.7640`	`-830.07940808`
`flowchan100`	`0.3330`	`0.00000000`
`flowchan200`	`1.0650`	`0.00000000`
`flowchan400`	`3.3790`	`0.00000000`
`gasoil100`	`0.4980`	`0.00523659`
`gasoil200`	`1.4750`	`0.00523660`
`gasoil400`	`7.0000`	`0.00523660`
`gasoil50`	`0.2010`	`0.00523664`
`glider100`	`1618.6330`	`-1255.05860055`
`glider50`	`76.3770`	`-1286.97737315`
`jbearing100`	`40.0780`	`-0.15504196`
`jbearing25`	`7.0120`	`-0.15401554`
`jbearing50`	`30.7210`	`-0.15482422`
`jbearing75`	`24.6340`	`-0.15498453`
`lnts100`	`0.3100`	`0.55459540`
`lnts200`	`1.4820`	`0.55457702`
`lnts400`	`6.4850`	`0.55457241`
`methanol100`	`0.8190`	`0.00902229`
`methanol200`	`2.5090`	`0.00902229`
`methanol400`	`8.4200`	`0.00902229`
`methanol50`	`1.2120`	`0.00902229`
`minsurf100`	`307.3960`	`2.50694926`
`minsurf25`	`5.7500`	`2.51948768`
`minsurf50`	`67.6010`	`2.51488916`
`minsurf75`	`155.1750`	`2.50568648`
`pinene100`	`2.3520`	`19.87217014`
`pinene200`	`10.7530`	`19.87216684`
`pinene25`	`1.1890`	`19.87216552`
`pinene50`	`1.0510`	`19.87216552`
`polygon100`	`21.3800`	`-0.78503127`
`polygon25`	`0.0360`	`-0.77973670`
`polygon50`	`1.6020`	`-0.78401305`
`polygon75`	`5.3170`	`-0.78478846`
`popdynm100`	`1.9540`	`19746.52860217`
`popdynm200`	`6.1400`	`19746.52964660`
`popdynm25`	`0.3130`	`19752.21541511`
`popdynm50`	`1.0690`	`19746.54515628`
`robot100`	`0.8920`	`9.14268538`
`robot200`	`7.1720`	`9.14139550`
`robot400`	`73.1190`	`9.14102603`
`robot50`	`0.1410`	`9.14687850`
`rocket100`	`0.7420`	`-1.01283202`
`rocket200`	`4.6100`	`-1.01283569`
`rocket400`	`40.4500`	`-1.01283661`
`torsion100`	`19.8940`	`-0.41823921`
`torsion25`	`1.5050`	`-0.41751073`
`torsion50`	`14.2930`	`-0.41808763`
`torsion75`	`12.4500`	`-0.41819940`

SNOPT: feasible:

Modelname	Time (SNOPT)	Obj (SNOPT)
`arki0014`	`3600.0370`	`-223972.99474775`
`arki0017`	`1715.7910`	`-121.83308010`
`arki0018`	`42.2100`	`0.01198069`
`arki0023`	`82.4830`	`-153.41732339`
`glider400`	`3599.9900`	`-252.52559804`

SNOPT: infeasible:

Modelname	Time (SNOPT)	Status (SNOPT)
`arki0008`	`--`	`mstat( 5) sstat( 1)`
`glider200`	`--`	`mstat( 5) sstat( 1)`
`infeas1`	`--`	`mstat( 4) sstat( 1)`

SNOPT: fail:

Modelname	Time (SNOPT)	Status (SNOPT)
`arki0003`	`--`	`mstat( 6) sstat( 4)`
`arki0016`	`--`	`mstat(13) sstat(13)`
`ex8_2_2`	`--`	`mstat( 6) sstat( 4)`

PATHNLP: locally optimal:

Modelname	Time (PATHNLP)	Obj (PATHNLP)
`arki0002`	`0.7480`	`1.87252775`
`arki0016`	`2.2560`	`867.97316601`
`arki0017`	`4.6620`	`-121.83308010`
`arki0018`	`1.9770`	`0.01045662`
`arki0020`	`0.3860`	`-41.07495436`
`arki0021`	`3.5850`	`-72.58210091`
`arki0022`	`8.1890`	`-87.09909127`
`arki0023`	`47.7820`	`-153.66007775`
`catmix100`	`0.2760`	`-0.04806942`
`catmix200`	`0.2730`	`-0.04805914`
`catmix400`	`1.8930`	`-0.04805655`
`catmix800`	`26.6930`	`-0.04805590`
`chain400`	`3.3930`	`5.06862169`
`ex8_2_3a`	`296.1640`	`-3731.07929210`
`flowchan100`	`0.1090`	`0.00000000`
`flowchan200`	`0.2300`	`0.00000000`
`flowchan400`	`0.4790`	`0.00000000`
`gasoil100`	`0.2320`	`0.00523659`
`gasoil200`	`0.7090`	`0.00523660`
`gasoil400`	`2.2940`	`0.00523660`
`gasoil50`	`0.1050`	`0.00523664`
`infeas1`	`1.6080`	`13685.59646388`
`jbearing100`	`0.5180`	`-0.15504196`
`jbearing25`	`0.1080`	`-0.15401554`
`jbearing50`	`0.3060`	`-0.15482422`
`jbearing75`	`0.3760`	`-0.15498453`
`lnts100`	`1.5830`	`0.55459540`
`lnts200`	`43.2490`	`0.55457702`
`methanol100`	`0.3380`	`0.00902229`
`methanol200`	`0.9810`	`0.00902229`
`methanol400`	`3.4380`	`0.00902229`
`methanol50`	`0.1280`	`0.00902229`
`minsurf100`	`0.6670`	`2.50694926`
`minsurf25`	`0.0920`	`2.51948768`
`minsurf50`	`0.2570`	`2.51488916`
`minsurf75`	`0.3910`	`2.50568648`
`pinene100`	`3.6530`	`19.87217015`
`pinene200`	`7.7290`	`19.87216684`
`pinene25`	`0.4780`	`19.87216552`
`pinene50`	`0.4680`	`19.87216552`
`polygon25`	`0.6940`	`-0.77967824`
`polygon75`	`14.0400`	`-0.75626662`
`popdynm100`	`2.0630`	`19746.52860217`
`popdynm200`	`6.5270`	`19746.52964660`
`popdynm25`	`0.1100`	`19752.21541511`
`popdynm50`	`0.5020`	`19746.54515628`
`robot100`	`0.9820`	`9.14268538`
`robot200`	`59.6580`	`9.14139550`
`robot400`	`52.1010`	`9.14102603`
`robot50`	`1.0190`	`9.14687850`
`torsion100`	`0.7090`	`-0.41823921`
`torsion25`	`0.0970`	`-0.41751073`
`torsion50`	`0.2700`	`-0.41808763`
`torsion75`	`0.4540`	`-0.41819940`

PATHNLP: feasible:

Modelname	Time (PATHNLP)	Obj (PATHNLP)
`arki0003`	`436.3120`	`624676.20567527`
`arki0004`	`952.6750`	`17730.41368439`
`arki0011`	`3602.5150`	`-224086.46003899`
`arki0015`	`252.1530`	`-180.93272868`
`camshape400`	`11.0170`	`-4.16698341`
`elec200`	`429.8600`	`22750.58850376`
`ex8_2_2`	`3952.3240`	`25.74674493`
`ex8_2_2a`	`1205.4070`	`-197.22299669`
`ex8_2_2b`	`443.2060`	`133.26074773`
`ex8_2_5a`	`280.6110`	`-454.77337863`
`ex8_2_5b`	`494.0380`	`-212.13223964`
`polygon100`	`548.4390`	`0.00000000`
`polygon50`	`64.0450`	`-0.65531628`

PATHNLP: fail:

Modelname	Time (PATHNLP)	Status (PATHNLP)
`arki0008`	`--`	`mstat( 6)sstat( 4)`
`arki0012`	`--`	`mstat(14)sstat( 9)`
`arki0013`	`--`	`mstat(14)sstat( 9)`
`arki0014`	`--`	`mstat(14)sstat( 9)`
`camshape800`	`--`	`mstat( 6)sstat( 4)`
`ex8_2_3b`	`--`	`mstat(13)sstat(13)`
`glider100`	`--`	`mstat(13)sstat(13)`
`glider200`	`--`	`mstat( 6)sstat( 4)`
`glider400`	`--`	`mstat( 6)sstat( 4)`
`glider50`	`--`	`mstat( 6)sstat( 4)`
`lnts400`	`--`	`mstat( 6)sstat( 4)`
`rocket100`	`--`	`mstat( 6)sstat( 4)`
`rocket200`	`--`	`mstat( 6)sstat( 4)`
`rocket400`	`--`	`mstat( 6)sstat( 4)`

SNOPT: all -- PATHNLP: all

A "(max)" behind a model names indicates that this model is a maximization model.

Modelname	Time (SNOPT)	Time (PATHNLP)	Ratio (SNOPT/ PATHNLP)	Obj (SNOPT)	Obj (PATHNLP)
`arki0002`	`155.9220`	`0.7480`	`208.452`	`1.09249984`	`1.87252775`
`arki0003`	`1.1860`	`436.3120`	---	`mstat( 6) sstat(4)`	`624676.20567527`
`arki0004`	`0.4440`	`952.6750`	`0.000`	`323.46703883`	`17730.41368439`
`arki0008`	`8.9820`	`596.2570`	---	`mstat( 5) sstat(1)`	`mstat( 6) sstat(4)`
`arki0011`	`417.8620`	`3602.5150`	`0.116`	`-224086.46000828`	`-224086.46003899`
`arki0012`	`3241.7210`	`0.0000`	---	`-224252.44559875`	`mstat(14) sstat(9)`
`arki0013`	`1487.5470`	`0.0000`	---	`-224253.08921843`	`mstat(14) sstat(9)`
`arki0014`	`3600.0370`	`0.0000`	---	`-223972.99474775`	`mstat(14) sstat(9)`
`arki0015`	`3.7150`	`252.1530`	`0.015`	`-272.29977820`	`-180.93272868`
`arki0016`	`NA`	`2.2560`	---	`mstat(13) sstat(13)`	`867.97316601`
`arki0017`	`1715.7910`	`4.6620`	`368.038`	`-121.83308010`	`-121.83308010`
`arki0018`	`42.2100`	`1.9770`	`21.351`	`0.01198069`	`0.01045662`
`arki0020`	`25.4230`	`0.3860`	`65.863`	`-41.07495436`	`-41.07495436`
`arki0021`	`75.6490`	`3.5850`	`21.102`	`-72.58210091`	`-72.58210091`
`arki0022`	`103.7290`	`8.1890`	`12.667`	`-87.09909127`	`-87.09909127`
`arki0023`	`82.4830`	`47.7820`	`1.726`	`-153.41732339`	`-153.66007775`
`camshape400`	`0.0960`	`11.0170`	`0.009`	`-4.27568692`	`-4.16698341`
`camshape800`	`0.4180`	`50.6430`	---	`-4.27427301`	`mstat( 6) sstat(4)`
`catmix100`	`0.1660`	`0.2760`	`0.601`	`-0.04806940`	`-0.04806942`
`catmix200`	`0.6780`	`0.2730`	`2.484`	`-0.04805914`	`-0.04805914`
`catmix400`	`2.5770`	`1.8930`	`1.361`	`-0.04805655`	`-0.04805655`
`catmix800`	`10.9170`	`26.6930`	`0.409`	`-0.04805590`	`-0.04805590`
`chain400`	`7.1580`	`3.3930`	`2.110`	`5.06862169`	`5.06862169`
`elec200`	`11.0000`	`429.8600`	`0.026`	`18438.99267601`	`22750.58850376`
`ex8_2_2`	`82.6420`	`3952.3240`	---	`mstat( 6) sstat(4)`	`25.74674493`
`ex8_2_2a`	`118.9230`	`1205.4070`	`0.099`	`-552.66024730`	`-197.22299669`
`ex8_2_2b`	`6.6280`	`443.2060`	`0.015`	`-551.76977066`	`133.26074773`
`ex8_2_3a`	`64.3650`	`296.1640`	`0.217`	`-3731.07808948`	`-3731.07929210`
`ex8_2_3b`	`22.1670`	`NA`	---	`-3730.72924771`	`mstat(13) sstat(13)`
`ex8_2_5a`	`183.9390`	`280.6110`	`0.655`	`-830.33802819`	`-454.77337863`
`ex8_2_5b`	`6.7640`	`494.0380`	`0.014`	`-830.07940808`	`-212.13223964`
`flowchan100`	`0.3330`	`0.1090`	`3.055`	`0.00000000`	`0.00000000`
`flowchan200`	`1.0650`	`0.2300`	`4.630`	`0.00000000`	`0.00000000`
`flowchan400`	`3.3790`	`0.4790`	`7.054`	`0.00000000`	`0.00000000`
`gasoil100`	`0.4980`	`0.2320`	`2.147`	`0.00523659`	`0.00523659`
`gasoil200`	`1.4750`	`0.7090`	`2.080`	`0.00523660`	`0.00523660`
`gasoil400`	`7.0000`	`2.2940`	`3.051`	`0.00523660`	`0.00523660`
`gasoil50`	`0.2010`	`0.1050`	`1.914`	`0.00523664`	`0.00523664`
`glider100`	`1618.6330`	`NA`	---	`-1255.05860055`	`mstat(13) sstat(13)`
`glider200`	`1.8010`	`406.4660`	---	`mstat( 5) sstat(1)`	`mstat( 6) sstat(4)`
`glider400`	`3599.9900`	`2768.1960`	---	`-252.52559804`	`mstat( 6) sstat(4)`
`glider50`	`76.3770`	`48.7000`	---	`-1286.97737315`	`mstat( 6) sstat(4)`
`infeas1 (max)`	`0.0160`	`1.6080`	---	`mstat( 4) sstat(1)`	`13685.59646388`
`jbearing100`	`40.0780`	`0.5180`	`77.371`	`-0.15504196`	`-0.15504196`
`jbearing25`	`7.0120`	`0.1080`	`64.926`	`-0.15401554`	`-0.15401554`
`jbearing50`	`30.7210`	`0.3060`	`100.395`	`-0.15482422`	`-0.15482422`
`jbearing75`	`24.6340`	`0.3760`	`65.516`	`-0.15498453`	`-0.15498453`
`lnts100`	`0.3100`	`1.5830`	`0.196`	`0.55459540`	`0.55459540`
`lnts200`	`1.4820`	`43.2490`	`0.034`	`0.55457702`	`0.55457702`
`lnts400`	`6.4850`	`289.8090`	---	`0.55457241`	`mstat( 6) sstat(4)`
`methanol100`	`0.8190`	`0.3380`	`2.423`	`0.00902229`	`0.00902229`
`methanol200`	`2.5090`	`0.9810`	`2.558`	`0.00902229`	`0.00902229`
`methanol400`	`8.4200`	`3.4380`	`2.449`	`0.00902229`	`0.00902229`
`methanol50`	`1.2120`	`0.1280`	`9.469`	`0.00902229`	`0.00902229`
`minsurf100`	`307.3960`	`0.6670`	`460.864`	`2.50694926`	`2.50694926`
`minsurf25`	`5.7500`	`0.0920`	`62.500`	`2.51948768`	`2.51948768`
`minsurf50`	`67.6010`	`0.2570`	`263.039`	`2.51488916`	`2.51488916`
`minsurf75`	`155.1750`	`0.3910`	`396.867`	`2.50568648`	`2.50568648`
`pinene100`	`2.3520`	`3.6530`	`0.644`	`19.87217014`	`19.87217015`
`pinene200`	`10.7530`	`7.7290`	`1.391`	`19.87216684`	`19.87216684`
`pinene25`	`1.1890`	`0.4780`	`2.487`	`19.87216552`	`19.87216552`
`pinene50`	`1.0510`	`0.4680`	`2.246`	`19.87216552`	`19.87216552`
`polygon100`	`21.3800`	`548.4390`	`0.039`	`-0.78503127`	`0.00000000`
`polygon25`	`0.0360`	`0.6940`	`0.052`	`-0.77973670`	`-0.77967824`
`polygon50`	`1.6020`	`64.0450`	`0.025`	`-0.78401305`	`-0.65531628`
`polygon75`	`5.3170`	`14.0400`	`0.379`	`-0.78478846`	`-0.75626662`
`popdynm100`	`1.9540`	`2.0630`	`0.947`	`19746.52860217`	`19746.52860217`
`popdynm200`	`6.1400`	`6.5270`	`0.941`	`19746.52964660`	`19746.52964660`
`popdynm25`	`0.3130`	`0.1100`	`2.845`	`19752.21541511`	`19752.21541511`
`popdynm50`	`1.0690`	`0.5020`	`2.129`	`19746.54515628`	`19746.54515628`
`robot100`	`0.8920`	`0.9820`	`0.908`	`9.14268538`	`9.14268538`
`robot200`	`7.1720`	`59.6580`	`0.120`	`9.14139550`	`9.14139550`
`robot400`	`73.1190`	`52.1010`	`1.403`	`9.14102603`	`9.14102603`
`robot50`	`0.1410`	`1.0190`	`0.138`	`9.14687850`	`9.14687850`
`rocket100`	`0.7420`	`52.5200`	---	`-1.01283202`	`mstat( 6) sstat(4)`
`rocket200`	`4.6100`	`137.1480`	---	`-1.01283569`	`mstat( 6) sstat(4)`
`rocket400`	`40.4500`	`983.9650`	---	`-1.01283661`	`mstat( 6) sstat(4)`
`torsion100`	`19.8940`	`0.7090`	`28.059`	`-0.41823921`	`-0.41823921`
`torsion25`	`1.5050`	`0.0970`	`15.515`	`-0.41751073`	`-0.41751073`
`torsion50`	`14.2930`	`0.2700`	`52.937`	`-0.41808763`	`-0.41808763`
`torsion75`	`12.4500`	`0.4540`	`27.423`	`-0.41819940`	`-0.41819940`