Solver Square Comparison

Solver Square Comparison: Considers all models.

Results created on 03/04/11 12:14:16 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 IPOPT-MA27 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:	IPOPT-1.trc
Tracefile 2:	PATHNLP-1.trc
Solvers used :	IPOPT-MA27
	PATHNLP
Modeltype(s)	`NLP`

	PATHNLP: optimal	PATHNLP: locally optimal	PATHNLP: feasible	PATHNLP: infeasible	PATHNLP: unbounded	PATHNLP: fail	PATHNLP: no data	total IPOPT-MA27
IPOPT-MA27: optimal	-	-	-	-	-	-	-	`-`
IPOPT-MA27: locally optimal	-	`52`	`12`	-	-	`11`	-	`75`
IPOPT-MA27: feasible	-	-	-	-	-	-	-	`-`
IPOPT-MA27: infeasible	-	-	-	-	-	`2`	-	`2`
IPOPT-MA27: unbounded	-	-	-	-	-	-	-	`-`
IPOPT-MA27: fail	-	`2`	`1`	-	-	`1`	-	`4`
IPOPT-MA27: 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.

IPOPT-MA27: locally optimal -- PATHNLP: locally optimal

Modelname	Time (IPOPT-MA27)	Time (PATHNLP)	Ratio (IPOPT-MA27/PATHNLP)	Obj (IPOPT-MA27)	Obj (PATHNLP)
`arki0002`	`0.1360`	`0.7480`	`0.182`	`1.87252774`	`1.87252775`
`arki0016`	`9.5800`	`2.2560`	`4.246`	`867.97316601`	`867.97316601`
`arki0017`	`0.4350`	`4.6620`	`0.093`	`-121.83308011`	`-121.83308010`
`arki0018`	`0.3290`	`1.9770`	`0.166`	`0.01045662`	`0.01045662`
`arki0020`	`0.0740`	`0.3860`	`0.192`	`-41.07495436`	`-41.07495436`
`arki0021`	`0.2110`	`3.5850`	`0.059`	`-72.58210091`	`-72.58210091`
`arki0022`	`0.3720`	`8.1890`	`0.045`	`-87.09909127`	`-87.09909127`
`arki0023`	`0.7280`	`47.7820`	`0.015`	`-153.66007775`	`-153.66007775`
`catmix100`	`0.0480`	`0.2760`	`0.174`	`-0.04806941`	`-0.04806942`
`catmix200`	`0.0520`	`0.2730`	`0.190`	`-0.04805914`	`-0.04805914`
`catmix400`	`0.0950`	`1.8930`	`0.050`	`-0.04805654`	`-0.04805655`
`catmix800`	`0.1810`	`26.6930`	`0.007`	`-0.04805590`	`-0.04805590`
`chain400`	`0.0170`	`3.3930`	`0.005`	`5.06862169`	`5.06862169`
`ex8_2_3a`	`2.8440`	`296.1640`	`0.010`	`-3731.07929678`	`-3731.07929210`
`flowchan100`	`0.0450`	`0.1090`	`0.413`	`0.00000000`	`0.00000000`
`flowchan200`	`0.0910`	`0.2300`	`0.396`	`0.00000000`	`0.00000000`
`flowchan400`	`0.1880`	`0.4790`	`0.392`	`0.00000000`	`0.00000000`
`gasoil100`	`0.1450`	`0.2320`	`0.625`	`0.00523659`	`0.00523659`
`gasoil200`	`0.2910`	`0.7090`	`0.410`	`0.00523660`	`0.00523660`
`gasoil400`	`0.7990`	`2.2940`	`0.348`	`0.00523660`	`0.00523660`
`gasoil50`	`0.0580`	`0.1050`	`0.552`	`0.00523664`	`0.00523664`
`infeas1`	`0.3510`	`1.6080`	`0.218`	`13685.59647017`	`13685.59646388`
`jbearing100`	`0.4680`	`0.5180`	`0.903`	`-0.15504194`	`-0.15504196`
`jbearing25`	`0.1140`	`0.1080`	`1.056`	`-0.15401551`	`-0.15401554`
`jbearing50`	`0.2000`	`0.3060`	`0.654`	`-0.15482381`	`-0.15482422`
`jbearing75`	`0.3240`	`0.3760`	`0.862`	`-0.15498446`	`-0.15498453`
`lnts100`	`0.0310`	`1.5830`	`0.020`	`0.55459540`	`0.55459540`
`lnts200`	`0.0460`	`43.2490`	`0.001`	`0.55457702`	`0.55457702`
`methanol100`	`0.1940`	`0.3380`	`0.574`	`0.00902229`	`0.00902229`
`methanol200`	`6.4270`	`0.9810`	`6.551`	`0.00902229`	`0.00902229`
`methanol400`	`2.8960`	`3.4380`	`0.842`	`0.00902229`	`0.00902229`
`methanol50`	`0.0700`	`0.1280`	`0.547`	`0.00902229`	`0.00902229`
`minsurf100`	`0.5960`	`0.6670`	`0.894`	`2.50694962`	`2.50694926`
`minsurf25`	`0.1270`	`0.0920`	`1.380`	`2.51948798`	`2.51948768`
`minsurf50`	`0.2730`	`0.2570`	`1.062`	`2.51489003`	`2.51488916`
`minsurf75`	`1.4340`	`0.3910`	`3.668`	`2.50568711`	`2.50568648`
`pinene100`	`0.1510`	`3.6530`	`0.041`	`19.87217015`	`19.87217015`
`pinene200`	`0.3690`	`7.7290`	`0.048`	`19.87216684`	`19.87216684`
`pinene25`	`0.0750`	`0.4780`	`0.157`	`19.87216552`	`19.87216552`
`pinene50`	`0.0750`	`0.4680`	`0.160`	`19.87216552`	`19.87216552`
`polygon25`	`0.0330`	`0.6940`	`0.048`	`-0.77974054`	`-0.77967824`
`polygon75`	`0.6500`	`14.0400`	`0.046`	`-0.78446376`	`-0.75626662`
`popdynm100`	`0.2190`	`2.0630`	`0.106`	`19746.52860214`	`19746.52860217`
`popdynm200`	`0.4940`	`6.5270`	`0.076`	`19746.52964658`	`19746.52964660`
`popdynm25`	`0.0870`	`0.1100`	`0.791`	`19752.21541508`	`19752.21541511`
`popdynm50`	`0.0980`	`0.5020`	`0.195`	`19746.54515625`	`19746.54515628`
`robot200`	`0.2420`	`59.6580`	`0.004`	`9.14139686`	`9.14139550`
`robot400`	`0.5500`	`52.1010`	`0.011`	`9.14102607`	`9.14102603`
`torsion100`	`0.5980`	`0.7090`	`0.843`	`-0.41823920`	`-0.41823921`
`torsion25`	`0.1220`	`0.0970`	`1.258`	`-0.41751073`	`-0.41751073`
`torsion50`	`0.2840`	`0.2700`	`1.052`	`-0.41808762`	`-0.41808763`
`torsion75`	`0.4420`	`0.4540`	`0.974`	`-0.41819939`	`-0.41819940`

IPOPT-MA27: locally optimal -- PATHNLP: feasible

Modelname	Time (IPOPT-MA27)	Time (PATHNLP)	Ratio (IPOPT-MA27/PATHNLP)	Obj (IPOPT-MA27)	Obj (PATHNLP)
`arki0003`	`510.2660`	`436.3120`	`1.169`	`3795.20602092`	`624676.20567527`
`arki0004`	`1.7070`	`952.6750`	`0.002`	`327.73301340`	`17730.41368439`
`arki0011`	`84.0000`	`3602.5150`	`0.023`	`-224086.46003209`	`-224086.46003899`
`arki0015`	`1.3560`	`252.1530`	`0.005`	`-266.94068809`	`-180.93272868`
`camshape400`	`0.1710`	`11.0170`	`0.016`	`-4.27569663`	`-4.16698341`
`elec200`	`26.1160`	`429.8600`	`0.061`	`18439.26774952`	`22750.58850376`
`ex8_2_2a`	`1.3160`	`1205.4070`	`0.001`	`-552.66625903`	`-197.22299669`
`ex8_2_2b`	`1.6600`	`443.2060`	`0.004`	`-552.66625998`	`133.26074773`
`ex8_2_5a`	`1.7680`	`280.6110`	`0.006`	`-830.33806763`	`-454.77337863`
`ex8_2_5b`	`1.9290`	`494.0380`	`0.004`	`-830.33806763`	`-212.13223964`
`polygon100`	`0.5510`	`548.4390`	`0.001`	`-0.78505614`	`0.00000000`
`polygon50`	`0.2900`	`64.0450`	`0.005`	`-0.78213256`	`-0.65531628`

IPOPT-MA27: locally optimal -- PATHNLP: fail

Modelname	Time (IPOPT-MA27)	Time (PATHNLP)	Ratio (IPOPT-MA27/PATHNLP)	Obj (IPOPT-MA27)	Status (PATHNLP)
`arki0012`	`55.7840`	`0.0000`	---	`-224252.42629883`	`mstat(14)sstat( 9)`
`arki0013`	`59.4700`	`0.0000`	---	`-224253.08789432`	`mstat(14)sstat( 9)`
`arki0014`	`50.4430`	`0.0000`	---	`-223977.03530616`	`mstat(14)sstat( 9)`
`camshape800`	`0.7280`	`50.6430`	---	`-4.27430687`	`mstat( 6)sstat( 4)`
`ex8_2_3b`	`3.4640`	`NA`	---	`-3731.07929695`	`mstat(13)sstat(13)`
`glider100`	`288.4420`	`NA`	---	`-1254.61354071`	`mstat(13)sstat(13)`
`glider50`	`24.8520`	`48.7000`	---	`-1286.97737317`	`mstat( 6)sstat( 4)`
`lnts400`	`0.0810`	`289.8090`	---	`0.55457241`	`mstat( 6)sstat( 4)`
`rocket100`	`1.9140`	`52.5200`	---	`-1.01283202`	`mstat( 6)sstat( 4)`
`rocket200`	`11.8530`	`137.1480`	---	`-1.01283569`	`mstat( 6)sstat( 4)`
`rocket400`	`118.2370`	`983.9650`	---	`-1.01283661`	`mstat( 6)sstat( 4)`

IPOPT-MA27: infeasible -- PATHNLP: fail

Modelname	Time (IPOPT-MA27)	Time (PATHNLP)	Ratio (IPOPT-MA27/PATHNLP)	Status (IPOPT-MA27)	Status (PATHNLP)
`glider200`	`1223.1610`	`406.4660`	---	`mstat( 5)sstat( 1)`	`mstat( 6)sstat( 4)`
`glider400`	`133.0970`	`2768.1960`	---	`mstat( 5)sstat( 1)`	`mstat( 6)sstat( 4)`

IPOPT-MA27: fail -- PATHNLP: locally optimal

Modelname	Time (IPOPT-MA27)	Time (PATHNLP)	Ratio (IPOPT-MA27/PATHNLP)	Status (IPOPT-MA27)	Obj (PATHNLP)
`robot100`	`3610.6280`	`0.9820`	---	`mstat( 6)sstat( 3)`	`9.14268538`
`robot50`	`3646.7020`	`1.0190`	---	`mstat( 6)sstat( 3)`	`9.14687850`

IPOPT-MA27: fail -- PATHNLP: feasible

Modelname	Time (IPOPT-MA27)	Time (PATHNLP)	Ratio (IPOPT-MA27/PATHNLP)	Status (IPOPT-MA27)	Obj (PATHNLP)
`ex8_2_2`	`3617.6920`	`3952.3240`	---	`mstat( 6)sstat( 3)`	`25.74674493`

IPOPT-MA27: fail -- PATHNLP: fail

Modelname	Time (IPOPT-MA27)	Time (PATHNLP)	Ratio (IPOPT-MA27/PATHNLP)	Status (IPOPT-MA27)	Status (PATHNLP)
`arki0008`	`3881.9600`	`596.2570`	---	`mstat( 6)sstat( 3)`	`mstat( 6)sstat( 4)`

IPOPT-MA27: locally optimal:

Modelname	Time (IPOPT-MA27)	Obj (IPOPT-MA27)
`arki0002`	`0.1360`	`1.87252774`
`arki0003`	`510.2660`	`3795.20602092`
`arki0004`	`1.7070`	`327.73301340`
`arki0011`	`84.0000`	`-224086.46003209`
`arki0012`	`55.7840`	`-224252.42629883`
`arki0013`	`59.4700`	`-224253.08789432`
`arki0014`	`50.4430`	`-223977.03530616`
`arki0015`	`1.3560`	`-266.94068809`
`arki0016`	`9.5800`	`867.97316601`
`arki0017`	`0.4350`	`-121.83308011`
`arki0018`	`0.3290`	`0.01045662`
`arki0020`	`0.0740`	`-41.07495436`
`arki0021`	`0.2110`	`-72.58210091`
`arki0022`	`0.3720`	`-87.09909127`
`arki0023`	`0.7280`	`-153.66007775`
`camshape400`	`0.1710`	`-4.27569663`
`camshape800`	`0.7280`	`-4.27430687`
`catmix100`	`0.0480`	`-0.04806941`
`catmix200`	`0.0520`	`-0.04805914`
`catmix400`	`0.0950`	`-0.04805654`
`catmix800`	`0.1810`	`-0.04805590`
`chain400`	`0.0170`	`5.06862169`
`elec200`	`26.1160`	`18439.26774952`
`ex8_2_2a`	`1.3160`	`-552.66625903`
`ex8_2_2b`	`1.6600`	`-552.66625998`
`ex8_2_3a`	`2.8440`	`-3731.07929678`
`ex8_2_3b`	`3.4640`	`-3731.07929695`
`ex8_2_5a`	`1.7680`	`-830.33806763`
`ex8_2_5b`	`1.9290`	`-830.33806763`
`flowchan100`	`0.0450`	`0.00000000`
`flowchan200`	`0.0910`	`0.00000000`
`flowchan400`	`0.1880`	`0.00000000`
`gasoil100`	`0.1450`	`0.00523659`
`gasoil200`	`0.2910`	`0.00523660`
`gasoil400`	`0.7990`	`0.00523660`
`gasoil50`	`0.0580`	`0.00523664`
`glider100`	`288.4420`	`-1254.61354071`
`glider50`	`24.8520`	`-1286.97737317`
`infeas1`	`0.3510`	`13685.59647017`
`jbearing100`	`0.4680`	`-0.15504194`
`jbearing25`	`0.1140`	`-0.15401551`
`jbearing50`	`0.2000`	`-0.15482381`
`jbearing75`	`0.3240`	`-0.15498446`
`lnts100`	`0.0310`	`0.55459540`
`lnts200`	`0.0460`	`0.55457702`
`lnts400`	`0.0810`	`0.55457241`
`methanol100`	`0.1940`	`0.00902229`
`methanol200`	`6.4270`	`0.00902229`
`methanol400`	`2.8960`	`0.00902229`
`methanol50`	`0.0700`	`0.00902229`
`minsurf100`	`0.5960`	`2.50694962`
`minsurf25`	`0.1270`	`2.51948798`
`minsurf50`	`0.2730`	`2.51489003`
`minsurf75`	`1.4340`	`2.50568711`
`pinene100`	`0.1510`	`19.87217015`
`pinene200`	`0.3690`	`19.87216684`
`pinene25`	`0.0750`	`19.87216552`
`pinene50`	`0.0750`	`19.87216552`
`polygon100`	`0.5510`	`-0.78505614`
`polygon25`	`0.0330`	`-0.77974054`
`polygon50`	`0.2900`	`-0.78213256`
`polygon75`	`0.6500`	`-0.78446376`
`popdynm100`	`0.2190`	`19746.52860214`
`popdynm200`	`0.4940`	`19746.52964658`
`popdynm25`	`0.0870`	`19752.21541508`
`popdynm50`	`0.0980`	`19746.54515625`
`robot200`	`0.2420`	`9.14139686`
`robot400`	`0.5500`	`9.14102607`
`rocket100`	`1.9140`	`-1.01283202`
`rocket200`	`11.8530`	`-1.01283569`
`rocket400`	`118.2370`	`-1.01283661`
`torsion100`	`0.5980`	`-0.41823920`
`torsion25`	`0.1220`	`-0.41751073`
`torsion50`	`0.2840`	`-0.41808762`
`torsion75`	`0.4420`	`-0.41819939`

IPOPT-MA27: infeasible:

Modelname	Time (IPOPT-MA27)	Status (IPOPT-MA27)
`glider200`	`--`	`mstat( 5) sstat( 1)`
`glider400`	`--`	`mstat( 5) sstat( 1)`

IPOPT-MA27: fail:

Modelname	Time (IPOPT-MA27)	Status (IPOPT-MA27)
`arki0008`	`--`	`mstat( 6) sstat( 3)`
`ex8_2_2`	`--`	`mstat( 6) sstat( 3)`
`robot100`	`--`	`mstat( 6) sstat( 3)`
`robot50`	`--`	`mstat( 6) sstat( 3)`

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)`

IPOPT-MA27: all -- PATHNLP: all

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

Modelname	Time (IPOPT-MA27)	Time (PATHNLP)	Ratio (IPOPT-MA27/ PATHNLP)	Obj (IPOPT-MA27)	Obj (PATHNLP)
`arki0002`	`0.1360`	`0.7480`	`0.182`	`1.87252774`	`1.87252775`
`arki0003`	`510.2660`	`436.3120`	`1.169`	`3795.20602092`	`624676.20567527`
`arki0004`	`1.7070`	`952.6750`	`0.002`	`327.73301340`	`17730.41368439`
`arki0008`	`3881.9600`	`596.2570`	---	`mstat( 6) sstat(3)`	`mstat( 6) sstat(4)`
`arki0011`	`84.0000`	`3602.5150`	`0.023`	`-224086.46003209`	`-224086.46003899`
`arki0012`	`55.7840`	`0.0000`	---	`-224252.42629883`	`mstat(14) sstat(9)`
`arki0013`	`59.4700`	`0.0000`	---	`-224253.08789432`	`mstat(14) sstat(9)`
`arki0014`	`50.4430`	`0.0000`	---	`-223977.03530616`	`mstat(14) sstat(9)`
`arki0015`	`1.3560`	`252.1530`	`0.005`	`-266.94068809`	`-180.93272868`
`arki0016`	`9.5800`	`2.2560`	`4.246`	`867.97316601`	`867.97316601`
`arki0017`	`0.4350`	`4.6620`	`0.093`	`-121.83308011`	`-121.83308010`
`arki0018`	`0.3290`	`1.9770`	`0.166`	`0.01045662`	`0.01045662`
`arki0020`	`0.0740`	`0.3860`	`0.192`	`-41.07495436`	`-41.07495436`
`arki0021`	`0.2110`	`3.5850`	`0.059`	`-72.58210091`	`-72.58210091`
`arki0022`	`0.3720`	`8.1890`	`0.045`	`-87.09909127`	`-87.09909127`
`arki0023`	`0.7280`	`47.7820`	`0.015`	`-153.66007775`	`-153.66007775`
`camshape400`	`0.1710`	`11.0170`	`0.016`	`-4.27569663`	`-4.16698341`
`camshape800`	`0.7280`	`50.6430`	---	`-4.27430687`	`mstat( 6) sstat(4)`
`catmix100`	`0.0480`	`0.2760`	`0.174`	`-0.04806941`	`-0.04806942`
`catmix200`	`0.0520`	`0.2730`	`0.190`	`-0.04805914`	`-0.04805914`
`catmix400`	`0.0950`	`1.8930`	`0.050`	`-0.04805654`	`-0.04805655`
`catmix800`	`0.1810`	`26.6930`	`0.007`	`-0.04805590`	`-0.04805590`
`chain400`	`0.0170`	`3.3930`	`0.005`	`5.06862169`	`5.06862169`
`elec200`	`26.1160`	`429.8600`	`0.061`	`18439.26774952`	`22750.58850376`
`ex8_2_2`	`3617.6920`	`3952.3240`	---	`mstat( 6) sstat(3)`	`25.74674493`
`ex8_2_2a`	`1.3160`	`1205.4070`	`0.001`	`-552.66625903`	`-197.22299669`
`ex8_2_2b`	`1.6600`	`443.2060`	`0.004`	`-552.66625998`	`133.26074773`
`ex8_2_3a`	`2.8440`	`296.1640`	`0.010`	`-3731.07929678`	`-3731.07929210`
`ex8_2_3b`	`3.4640`	`NA`	---	`-3731.07929695`	`mstat(13) sstat(13)`
`ex8_2_5a`	`1.7680`	`280.6110`	`0.006`	`-830.33806763`	`-454.77337863`
`ex8_2_5b`	`1.9290`	`494.0380`	`0.004`	`-830.33806763`	`-212.13223964`
`flowchan100`	`0.0450`	`0.1090`	`0.413`	`0.00000000`	`0.00000000`
`flowchan200`	`0.0910`	`0.2300`	`0.396`	`0.00000000`	`0.00000000`
`flowchan400`	`0.1880`	`0.4790`	`0.392`	`0.00000000`	`0.00000000`
`gasoil100`	`0.1450`	`0.2320`	`0.625`	`0.00523659`	`0.00523659`
`gasoil200`	`0.2910`	`0.7090`	`0.410`	`0.00523660`	`0.00523660`
`gasoil400`	`0.7990`	`2.2940`	`0.348`	`0.00523660`	`0.00523660`
`gasoil50`	`0.0580`	`0.1050`	`0.552`	`0.00523664`	`0.00523664`
`glider100`	`288.4420`	`NA`	---	`-1254.61354071`	`mstat(13) sstat(13)`
`glider200`	`1223.1610`	`406.4660`	---	`mstat( 5) sstat(1)`	`mstat( 6) sstat(4)`
`glider400`	`133.0970`	`2768.1960`	---	`mstat( 5) sstat(1)`	`mstat( 6) sstat(4)`
`glider50`	`24.8520`	`48.7000`	---	`-1286.97737317`	`mstat( 6) sstat(4)`
`infeas1 (max)`	`0.3510`	`1.6080`	`0.218`	`13685.59647017`	`13685.59646388`
`jbearing100`	`0.4680`	`0.5180`	`0.903`	`-0.15504194`	`-0.15504196`
`jbearing25`	`0.1140`	`0.1080`	`1.056`	`-0.15401551`	`-0.15401554`
`jbearing50`	`0.2000`	`0.3060`	`0.654`	`-0.15482381`	`-0.15482422`
`jbearing75`	`0.3240`	`0.3760`	`0.862`	`-0.15498446`	`-0.15498453`
`lnts100`	`0.0310`	`1.5830`	`0.020`	`0.55459540`	`0.55459540`
`lnts200`	`0.0460`	`43.2490`	`0.001`	`0.55457702`	`0.55457702`
`lnts400`	`0.0810`	`289.8090`	---	`0.55457241`	`mstat( 6) sstat(4)`
`methanol100`	`0.1940`	`0.3380`	`0.574`	`0.00902229`	`0.00902229`
`methanol200`	`6.4270`	`0.9810`	`6.551`	`0.00902229`	`0.00902229`
`methanol400`	`2.8960`	`3.4380`	`0.842`	`0.00902229`	`0.00902229`
`methanol50`	`0.0700`	`0.1280`	`0.547`	`0.00902229`	`0.00902229`
`minsurf100`	`0.5960`	`0.6670`	`0.894`	`2.50694962`	`2.50694926`
`minsurf25`	`0.1270`	`0.0920`	`1.380`	`2.51948798`	`2.51948768`
`minsurf50`	`0.2730`	`0.2570`	`1.062`	`2.51489003`	`2.51488916`
`minsurf75`	`1.4340`	`0.3910`	`3.668`	`2.50568711`	`2.50568648`
`pinene100`	`0.1510`	`3.6530`	`0.041`	`19.87217015`	`19.87217015`
`pinene200`	`0.3690`	`7.7290`	`0.048`	`19.87216684`	`19.87216684`
`pinene25`	`0.0750`	`0.4780`	`0.157`	`19.87216552`	`19.87216552`
`pinene50`	`0.0750`	`0.4680`	`0.160`	`19.87216552`	`19.87216552`
`polygon100`	`0.5510`	`548.4390`	`0.001`	`-0.78505614`	`0.00000000`
`polygon25`	`0.0330`	`0.6940`	`0.048`	`-0.77974054`	`-0.77967824`
`polygon50`	`0.2900`	`64.0450`	`0.005`	`-0.78213256`	`-0.65531628`
`polygon75`	`0.6500`	`14.0400`	`0.046`	`-0.78446376`	`-0.75626662`
`popdynm100`	`0.2190`	`2.0630`	`0.106`	`19746.52860214`	`19746.52860217`
`popdynm200`	`0.4940`	`6.5270`	`0.076`	`19746.52964658`	`19746.52964660`
`popdynm25`	`0.0870`	`0.1100`	`0.791`	`19752.21541508`	`19752.21541511`
`popdynm50`	`0.0980`	`0.5020`	`0.195`	`19746.54515625`	`19746.54515628`
`robot100`	`3610.6280`	`0.9820`	---	`mstat( 6) sstat(3)`	`9.14268538`
`robot200`	`0.2420`	`59.6580`	`0.004`	`9.14139686`	`9.14139550`
`robot400`	`0.5500`	`52.1010`	`0.011`	`9.14102607`	`9.14102603`
`robot50`	`3646.7020`	`1.0190`	---	`mstat( 6) sstat(3)`	`9.14687850`
`rocket100`	`1.9140`	`52.5200`	---	`-1.01283202`	`mstat( 6) sstat(4)`
`rocket200`	`11.8530`	`137.1480`	---	`-1.01283569`	`mstat( 6) sstat(4)`
`rocket400`	`118.2370`	`983.9650`	---	`-1.01283661`	`mstat( 6) sstat(4)`
`torsion100`	`0.5980`	`0.7090`	`0.843`	`-0.41823920`	`-0.41823921`
`torsion25`	`0.1220`	`0.0970`	`1.258`	`-0.41751073`	`-0.41751073`
`torsion50`	`0.2840`	`0.2700`	`1.052`	`-0.41808762`	`-0.41808763`
`torsion75`	`0.4420`	`0.4540`	`0.974`	`-0.41819939`	`-0.41819940`