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 CONOPT 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:	CONOPT-1.trc
Tracefile 2:	PATHNLP-1.trc
Solvers used :	CONOPT
	PATHNLP
Modeltype(s)	`NLP`

	PATHNLP: optimal	PATHNLP: locally optimal	PATHNLP: feasible	PATHNLP: infeasible	PATHNLP: unbounded	PATHNLP: fail	PATHNLP: no data	total CONOPT
CONOPT: optimal	-	-	-	-	-	-	-	`-`
CONOPT: locally optimal	-	`54`	`12`	-	-	`6`	-	`72`
CONOPT: feasible	-	-	-	-	-	`1`	-	`1`
CONOPT: infeasible	-	-	-	-	-	`3`	-	`3`
CONOPT: unbounded	-	-	`1`	-	-	-	-	`1`
CONOPT: fail	-	-	-	-	-	`4`	-	`4`
CONOPT: 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.

CONOPT: locally optimal -- PATHNLP: locally optimal

Modelname	Time (CONOPT)	Time (PATHNLP)	Ratio (CONOPT/PATHNLP)	Obj (CONOPT)	Obj (PATHNLP)
`arki0002`	`0.9630`	`0.7480`	`1.287`	`1.08668302`	`1.87252775`
`arki0016`	`1107.5970`	`2.2560`	`490.956`	`867.97316601`	`867.97316601`
`arki0017`	`94.5180`	`4.6620`	`20.274`	`-121.83308010`	`-121.83308010`
`arki0018`	`1.2720`	`1.9770`	`0.643`	`0.01045662`	`0.01045662`
`arki0020`	`0.2000`	`0.3860`	`0.518`	`-41.07495436`	`-41.07495436`
`arki0021`	`0.9070`	`3.5850`	`0.253`	`-72.58210091`	`-72.58210091`
`arki0022`	`1.1870`	`8.1890`	`0.145`	`-87.09909127`	`-87.09909127`
`arki0023`	`3.7120`	`47.7820`	`0.078`	`-153.66007775`	`-153.66007775`
`catmix100`	`0.0460`	`0.2760`	`0.167`	`-0.04806940`	`-0.04806942`
`catmix200`	`0.0550`	`0.2730`	`0.201`	`-0.04805914`	`-0.04805914`
`catmix400`	`0.1440`	`1.8930`	`0.076`	`-0.04805654`	`-0.04805655`
`catmix800`	`0.4500`	`26.6930`	`0.017`	`-0.04805590`	`-0.04805590`
`chain400`	`0.1190`	`3.3930`	`0.035`	`5.06862169`	`5.06862169`
`ex8_2_3a`	`20.6320`	`296.1640`	`0.070`	`-3731.07929501`	`-3731.07929210`
`flowchan100`	`0.0420`	`0.1090`	`0.385`	`0.00000000`	`0.00000000`
`flowchan200`	`0.1220`	`0.2300`	`0.530`	`0.00000000`	`0.00000000`
`flowchan400`	`0.2910`	`0.4790`	`0.608`	`0.00000000`	`0.00000000`
`gasoil100`	`0.1860`	`0.2320`	`0.802`	`0.00523659`	`0.00523659`
`gasoil200`	`0.3930`	`0.7090`	`0.554`	`0.00523660`	`0.00523660`
`gasoil400`	`0.8620`	`2.2940`	`0.376`	`0.00523660`	`0.00523660`
`gasoil50`	`0.0970`	`0.1050`	`0.924`	`0.00523664`	`0.00523664`
`infeas1`	`0.2410`	`1.6080`	`0.150`	`13685.59646095`	`13685.59646388`
`jbearing100`	`0.5080`	`0.5180`	`0.981`	`-0.15504196`	`-0.15504196`
`jbearing25`	`1.4170`	`0.1080`	`13.120`	`-0.15401554`	`-0.15401554`
`jbearing50`	`0.1920`	`0.3060`	`0.627`	`-0.15482422`	`-0.15482422`
`jbearing75`	`0.3430`	`0.3760`	`0.912`	`-0.15498453`	`-0.15498453`
`lnts100`	`0.1230`	`1.5830`	`0.078`	`0.55459540`	`0.55459540`
`lnts200`	`0.3110`	`43.2490`	`0.007`	`0.55457702`	`0.55457702`
`methanol100`	`0.1830`	`0.3380`	`0.541`	`0.00902229`	`0.00902229`
`methanol200`	`0.3870`	`0.9810`	`0.394`	`0.00902229`	`0.00902229`
`methanol400`	`0.9160`	`3.4380`	`0.266`	`0.00902229`	`0.00902229`
`methanol50`	`0.0910`	`0.1280`	`0.711`	`0.00902229`	`0.00902229`
`minsurf100`	`0.5520`	`0.6670`	`0.828`	`2.50694926`	`2.50694926`
`minsurf25`	`0.8990`	`0.0920`	`9.772`	`2.51948768`	`2.51948768`
`minsurf50`	`0.1680`	`0.2570`	`0.654`	`2.51488916`	`2.51488916`
`minsurf75`	`0.3050`	`0.3910`	`0.780`	`2.50568648`	`2.50568648`
`pinene100`	`0.3440`	`3.6530`	`0.094`	`19.87217014`	`19.87217015`
`pinene200`	`1.4160`	`7.7290`	`0.183`	`19.87216684`	`19.87216684`
`pinene25`	`0.2330`	`0.4780`	`0.487`	`19.87216067`	`19.87216552`
`pinene50`	`0.2330`	`0.4680`	`0.498`	`19.87216067`	`19.87216552`
`polygon25`	`0.1040`	`0.6940`	`0.150`	`-0.77825010`	`-0.77967824`
`polygon75`	`2.7700`	`14.0400`	`0.197`	`-0.78441600`	`-0.75626662`
`popdynm100`	`3.3110`	`2.0630`	`1.605`	`19746.52860217`	`19746.52860217`
`popdynm200`	`4.4270`	`6.5270`	`0.678`	`19746.52964660`	`19746.52964660`
`popdynm25`	`1.1360`	`0.1100`	`10.327`	`19752.21541511`	`19752.21541511`
`popdynm50`	`0.8220`	`0.5020`	`1.637`	`19746.54515628`	`19746.54515628`
`robot100`	`0.2140`	`0.9820`	`0.218`	`9.14268538`	`9.14268538`
`robot200`	`0.8580`	`59.6580`	`0.014`	`9.14139550`	`9.14139550`
`robot400`	`1.7430`	`52.1010`	`0.033`	`9.14102603`	`9.14102603`
`robot50`	`0.1010`	`1.0190`	`0.099`	`9.14687850`	`9.14687850`
`torsion100`	`2.8130`	`0.7090`	`3.968`	`-0.41823921`	`-0.41823921`
`torsion25`	`0.5190`	`0.0970`	`5.351`	`-0.41751073`	`-0.41751073`
`torsion50`	`1.1460`	`0.2700`	`4.244`	`-0.41808763`	`-0.41808763`
`torsion75`	`2.1170`	`0.4540`	`4.663`	`-0.41819940`	`-0.41819940`

CONOPT: locally optimal -- PATHNLP: feasible

Modelname	Time (CONOPT)	Time (PATHNLP)	Ratio (CONOPT/PATHNLP)	Obj (CONOPT)	Obj (PATHNLP)
`arki0003`	`5.0250`	`436.3120`	`0.012`	`3795.20606743`	`624676.20567527`
`arki0004`	`3.3540`	`952.6750`	`0.004`	`327.73301341`	`17730.41368439`
`arki0011`	`6.5860`	`3602.5150`	`0.002`	`-224086.46003881`	`-224086.46003899`
`arki0015`	`0.7570`	`252.1530`	`0.003`	`-271.73572350`	`-180.93272868`
`camshape400`	`0.0460`	`11.0170`	`0.004`	`-4.27568848`	`-4.16698341`
`elec200`	`9.6280`	`429.8600`	`0.022`	`18438.91507542`	`22750.58850376`
`ex8_2_2a`	`7.5910`	`1205.4070`	`0.006`	`-552.66625942`	`-197.22299669`
`ex8_2_2b`	`9.0010`	`443.2060`	`0.020`	`-552.66625902`	`133.26074773`
`ex8_2_5a`	`3.2450`	`280.6110`	`0.012`	`-830.33806704`	`-454.77337863`
`ex8_2_5b`	`2.9900`	`494.0380`	`0.006`	`-830.33806698`	`-212.13223964`
`polygon100`	`5.4050`	`548.4390`	`0.010`	`-0.78486056`	`0.00000000`
`polygon50`	`0.5740`	`64.0450`	`0.009`	`-0.78306429`	`-0.65531628`

CONOPT: locally optimal -- PATHNLP: fail

Modelname	Time (CONOPT)	Time (PATHNLP)	Ratio (CONOPT/PATHNLP)	Obj (CONOPT)	Status (PATHNLP)
`arki0013`	`745.9290`	`0.0000`	---	`-224253.08922164`	`mstat(14)sstat( 9)`
`camshape800`	`0.2300`	`50.6430`	---	`-4.27427414`	`mstat( 6)sstat( 4)`
`ex8_2_3b`	`20.5010`	`NA`	---	`-3731.07929518`	`mstat(13)sstat(13)`
`glider50`	`6.9400`	`48.7000`	---	`-1286.97737315`	`mstat( 6)sstat( 4)`
`lnts400`	`0.9830`	`289.8090`	---	`0.55457241`	`mstat( 6)sstat( 4)`
`rocket400`	`7.3270`	`983.9650`	---	`-1.01283660`	`mstat( 6)sstat( 4)`

CONOPT: feasible -- PATHNLP: fail

Modelname	Time (CONOPT)	Time (PATHNLP)	Ratio (CONOPT/PATHNLP)	Obj (CONOPT)	Status (PATHNLP)
`glider400`	`45.2300`	`2768.1960`	---	`-298.24695974`	`mstat( 6)sstat( 4)`

CONOPT: infeasible -- PATHNLP: fail

Modelname	Time (CONOPT)	Time (PATHNLP)	Ratio (CONOPT/PATHNLP)	Status (CONOPT)	Status (PATHNLP)
`arki0008`	`24.1840`	`596.2570`	---	`mstat( 5)sstat( 1)`	`mstat( 6)sstat( 4)`
`glider100`	`3.3770`	`NA`	---	`mstat( 5)sstat( 1)`	`mstat(13)sstat(13)`
`glider200`	`6.6630`	`406.4660`	---	`mstat( 5)sstat( 1)`	`mstat( 6)sstat( 4)`

CONOPT: unbounded -- PATHNLP: feasible

Modelname	Time (CONOPT)	Time (PATHNLP)	Ratio (CONOPT/PATHNLP)	Status (CONOPT)	Obj (PATHNLP)
`ex8_2_2`	`1.7750`	`3952.3240`	---	`mstat( 3)sstat( 1)`	`25.74674493`

CONOPT: fail -- PATHNLP: fail

Modelname	Time (CONOPT)	Time (PATHNLP)	Ratio (CONOPT/PATHNLP)	Status (CONOPT)	Status (PATHNLP)
`arki0012`	`15.0240`	`0.0000`	---	`mstat( 6)sstat( 4)`	`mstat(14)sstat( 9)`
`arki0014`	`11.0840`	`0.0000`	---	`mstat( 6)sstat( 4)`	`mstat(14)sstat( 9)`
`rocket100`	`0.6340`	`52.5200`	---	`mstat( 6)sstat( 4)`	`mstat( 6)sstat( 4)`
`rocket200`	`1.0570`	`137.1480`	---	`mstat( 6)sstat( 4)`	`mstat( 6)sstat( 4)`

CONOPT: locally optimal:

Modelname	Time (CONOPT)	Obj (CONOPT)
`arki0002`	`0.9630`	`1.08668302`
`arki0003`	`5.0250`	`3795.20606743`
`arki0004`	`3.3540`	`327.73301341`
`arki0011`	`6.5860`	`-224086.46003881`
`arki0013`	`745.9290`	`-224253.08922164`
`arki0015`	`0.7570`	`-271.73572350`
`arki0016`	`1107.5970`	`867.97316601`
`arki0017`	`94.5180`	`-121.83308010`
`arki0018`	`1.2720`	`0.01045662`
`arki0020`	`0.2000`	`-41.07495436`
`arki0021`	`0.9070`	`-72.58210091`
`arki0022`	`1.1870`	`-87.09909127`
`arki0023`	`3.7120`	`-153.66007775`
`camshape400`	`0.0460`	`-4.27568848`
`camshape800`	`0.2300`	`-4.27427414`
`catmix100`	`0.0460`	`-0.04806940`
`catmix200`	`0.0550`	`-0.04805914`
`catmix400`	`0.1440`	`-0.04805654`
`catmix800`	`0.4500`	`-0.04805590`
`chain400`	`0.1190`	`5.06862169`
`elec200`	`9.6280`	`18438.91507542`
`ex8_2_2a`	`7.5910`	`-552.66625942`
`ex8_2_2b`	`9.0010`	`-552.66625902`
`ex8_2_3a`	`20.6320`	`-3731.07929501`
`ex8_2_3b`	`20.5010`	`-3731.07929518`
`ex8_2_5a`	`3.2450`	`-830.33806704`
`ex8_2_5b`	`2.9900`	`-830.33806698`
`flowchan100`	`0.0420`	`0.00000000`
`flowchan200`	`0.1220`	`0.00000000`
`flowchan400`	`0.2910`	`0.00000000`
`gasoil100`	`0.1860`	`0.00523659`
`gasoil200`	`0.3930`	`0.00523660`
`gasoil400`	`0.8620`	`0.00523660`
`gasoil50`	`0.0970`	`0.00523664`
`glider50`	`6.9400`	`-1286.97737315`
`infeas1`	`0.2410`	`13685.59646095`
`jbearing100`	`0.5080`	`-0.15504196`
`jbearing25`	`1.4170`	`-0.15401554`
`jbearing50`	`0.1920`	`-0.15482422`
`jbearing75`	`0.3430`	`-0.15498453`
`lnts100`	`0.1230`	`0.55459540`
`lnts200`	`0.3110`	`0.55457702`
`lnts400`	`0.9830`	`0.55457241`
`methanol100`	`0.1830`	`0.00902229`
`methanol200`	`0.3870`	`0.00902229`
`methanol400`	`0.9160`	`0.00902229`
`methanol50`	`0.0910`	`0.00902229`
`minsurf100`	`0.5520`	`2.50694926`
`minsurf25`	`0.8990`	`2.51948768`
`minsurf50`	`0.1680`	`2.51488916`
`minsurf75`	`0.3050`	`2.50568648`
`pinene100`	`0.3440`	`19.87217014`
`pinene200`	`1.4160`	`19.87216684`
`pinene25`	`0.2330`	`19.87216067`
`pinene50`	`0.2330`	`19.87216067`
`polygon100`	`5.4050`	`-0.78486056`
`polygon25`	`0.1040`	`-0.77825010`
`polygon50`	`0.5740`	`-0.78306429`
`polygon75`	`2.7700`	`-0.78441600`
`popdynm100`	`3.3110`	`19746.52860217`
`popdynm200`	`4.4270`	`19746.52964660`
`popdynm25`	`1.1360`	`19752.21541511`
`popdynm50`	`0.8220`	`19746.54515628`
`robot100`	`0.2140`	`9.14268538`
`robot200`	`0.8580`	`9.14139550`
`robot400`	`1.7430`	`9.14102603`
`robot50`	`0.1010`	`9.14687850`
`rocket400`	`7.3270`	`-1.01283660`
`torsion100`	`2.8130`	`-0.41823921`
`torsion25`	`0.5190`	`-0.41751073`
`torsion50`	`1.1460`	`-0.41808763`
`torsion75`	`2.1170`	`-0.41819940`

CONOPT: feasible:

Modelname	Time (CONOPT)	Obj (CONOPT)
`glider400`	`45.2300`	`-298.24695974`

CONOPT: infeasible:

Modelname	Time (CONOPT)	Status (CONOPT)
`arki0008`	`--`	`mstat( 5) sstat( 1)`
`glider100`	`--`	`mstat( 5) sstat( 1)`
`glider200`	`--`	`mstat( 5) sstat( 1)`

CONOPT: unbounded:

Modelname	Time (CONOPT)	Status (CONOPT)
`ex8_2_2`	`1.7750`	`mstat( 3) sstat( 1)`

CONOPT: fail:

Modelname	Time (CONOPT)	Status (CONOPT)
`arki0012`	`--`	`mstat( 6) sstat( 4)`
`arki0014`	`--`	`mstat( 6) sstat( 4)`
`rocket100`	`--`	`mstat( 6) sstat( 4)`
`rocket200`	`--`	`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)`

CONOPT: all -- PATHNLP: all

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

Modelname	Time (CONOPT)	Time (PATHNLP)	Ratio (CONOPT/ PATHNLP)	Obj (CONOPT)	Obj (PATHNLP)
`arki0002`	`0.9630`	`0.7480`	`1.287`	`1.08668302`	`1.87252775`
`arki0003`	`5.0250`	`436.3120`	`0.012`	`3795.20606743`	`624676.20567527`
`arki0004`	`3.3540`	`952.6750`	`0.004`	`327.73301341`	`17730.41368439`
`arki0008`	`24.1840`	`596.2570`	---	`mstat( 5) sstat(1)`	`mstat( 6) sstat(4)`
`arki0011`	`6.5860`	`3602.5150`	`0.002`	`-224086.46003881`	`-224086.46003899`
`arki0012`	`15.0240`	`0.0000`	---	`mstat( 6) sstat(4)`	`mstat(14) sstat(9)`
`arki0013`	`745.9290`	`0.0000`	---	`-224253.08922164`	`mstat(14) sstat(9)`
`arki0014`	`11.0840`	`0.0000`	---	`mstat( 6) sstat(4)`	`mstat(14) sstat(9)`
`arki0015`	`0.7570`	`252.1530`	`0.003`	`-271.73572350`	`-180.93272868`
`arki0016`	`1107.5970`	`2.2560`	`490.956`	`867.97316601`	`867.97316601`
`arki0017`	`94.5180`	`4.6620`	`20.274`	`-121.83308010`	`-121.83308010`
`arki0018`	`1.2720`	`1.9770`	`0.643`	`0.01045662`	`0.01045662`
`arki0020`	`0.2000`	`0.3860`	`0.518`	`-41.07495436`	`-41.07495436`
`arki0021`	`0.9070`	`3.5850`	`0.253`	`-72.58210091`	`-72.58210091`
`arki0022`	`1.1870`	`8.1890`	`0.145`	`-87.09909127`	`-87.09909127`
`arki0023`	`3.7120`	`47.7820`	`0.078`	`-153.66007775`	`-153.66007775`
`camshape400`	`0.0460`	`11.0170`	`0.004`	`-4.27568848`	`-4.16698341`
`camshape800`	`0.2300`	`50.6430`	---	`-4.27427414`	`mstat( 6) sstat(4)`
`catmix100`	`0.0460`	`0.2760`	`0.167`	`-0.04806940`	`-0.04806942`
`catmix200`	`0.0550`	`0.2730`	`0.201`	`-0.04805914`	`-0.04805914`
`catmix400`	`0.1440`	`1.8930`	`0.076`	`-0.04805654`	`-0.04805655`
`catmix800`	`0.4500`	`26.6930`	`0.017`	`-0.04805590`	`-0.04805590`
`chain400`	`0.1190`	`3.3930`	`0.035`	`5.06862169`	`5.06862169`
`elec200`	`9.6280`	`429.8600`	`0.022`	`18438.91507542`	`22750.58850376`
`ex8_2_2`	`1.7750`	`3952.3240`	---	`mstat( 3) sstat(1)`	`25.74674493`
`ex8_2_2a`	`7.5910`	`1205.4070`	`0.006`	`-552.66625942`	`-197.22299669`
`ex8_2_2b`	`9.0010`	`443.2060`	`0.020`	`-552.66625902`	`133.26074773`
`ex8_2_3a`	`20.6320`	`296.1640`	`0.070`	`-3731.07929501`	`-3731.07929210`
`ex8_2_3b`	`20.5010`	`NA`	---	`-3731.07929518`	`mstat(13) sstat(13)`
`ex8_2_5a`	`3.2450`	`280.6110`	`0.012`	`-830.33806704`	`-454.77337863`
`ex8_2_5b`	`2.9900`	`494.0380`	`0.006`	`-830.33806698`	`-212.13223964`
`flowchan100`	`0.0420`	`0.1090`	`0.385`	`0.00000000`	`0.00000000`
`flowchan200`	`0.1220`	`0.2300`	`0.530`	`0.00000000`	`0.00000000`
`flowchan400`	`0.2910`	`0.4790`	`0.608`	`0.00000000`	`0.00000000`
`gasoil100`	`0.1860`	`0.2320`	`0.802`	`0.00523659`	`0.00523659`
`gasoil200`	`0.3930`	`0.7090`	`0.554`	`0.00523660`	`0.00523660`
`gasoil400`	`0.8620`	`2.2940`	`0.376`	`0.00523660`	`0.00523660`
`gasoil50`	`0.0970`	`0.1050`	`0.924`	`0.00523664`	`0.00523664`
`glider100`	`3.3770`	`NA`	---	`mstat( 5) sstat(1)`	`mstat(13) sstat(13)`
`glider200`	`6.6630`	`406.4660`	---	`mstat( 5) sstat(1)`	`mstat( 6) sstat(4)`
`glider400`	`45.2300`	`2768.1960`	---	`-298.24695974`	`mstat( 6) sstat(4)`
`glider50`	`6.9400`	`48.7000`	---	`-1286.97737315`	`mstat( 6) sstat(4)`
`infeas1 (max)`	`0.2410`	`1.6080`	`0.150`	`13685.59646095`	`13685.59646388`
`jbearing100`	`0.5080`	`0.5180`	`0.981`	`-0.15504196`	`-0.15504196`
`jbearing25`	`1.4170`	`0.1080`	`13.120`	`-0.15401554`	`-0.15401554`
`jbearing50`	`0.1920`	`0.3060`	`0.627`	`-0.15482422`	`-0.15482422`
`jbearing75`	`0.3430`	`0.3760`	`0.912`	`-0.15498453`	`-0.15498453`
`lnts100`	`0.1230`	`1.5830`	`0.078`	`0.55459540`	`0.55459540`
`lnts200`	`0.3110`	`43.2490`	`0.007`	`0.55457702`	`0.55457702`
`lnts400`	`0.9830`	`289.8090`	---	`0.55457241`	`mstat( 6) sstat(4)`
`methanol100`	`0.1830`	`0.3380`	`0.541`	`0.00902229`	`0.00902229`
`methanol200`	`0.3870`	`0.9810`	`0.394`	`0.00902229`	`0.00902229`
`methanol400`	`0.9160`	`3.4380`	`0.266`	`0.00902229`	`0.00902229`
`methanol50`	`0.0910`	`0.1280`	`0.711`	`0.00902229`	`0.00902229`
`minsurf100`	`0.5520`	`0.6670`	`0.828`	`2.50694926`	`2.50694926`
`minsurf25`	`0.8990`	`0.0920`	`9.772`	`2.51948768`	`2.51948768`
`minsurf50`	`0.1680`	`0.2570`	`0.654`	`2.51488916`	`2.51488916`
`minsurf75`	`0.3050`	`0.3910`	`0.780`	`2.50568648`	`2.50568648`
`pinene100`	`0.3440`	`3.6530`	`0.094`	`19.87217014`	`19.87217015`
`pinene200`	`1.4160`	`7.7290`	`0.183`	`19.87216684`	`19.87216684`
`pinene25`	`0.2330`	`0.4780`	`0.487`	`19.87216067`	`19.87216552`
`pinene50`	`0.2330`	`0.4680`	`0.498`	`19.87216067`	`19.87216552`
`polygon100`	`5.4050`	`548.4390`	`0.010`	`-0.78486056`	`0.00000000`
`polygon25`	`0.1040`	`0.6940`	`0.150`	`-0.77825010`	`-0.77967824`
`polygon50`	`0.5740`	`64.0450`	`0.009`	`-0.78306429`	`-0.65531628`
`polygon75`	`2.7700`	`14.0400`	`0.197`	`-0.78441600`	`-0.75626662`
`popdynm100`	`3.3110`	`2.0630`	`1.605`	`19746.52860217`	`19746.52860217`
`popdynm200`	`4.4270`	`6.5270`	`0.678`	`19746.52964660`	`19746.52964660`
`popdynm25`	`1.1360`	`0.1100`	`10.327`	`19752.21541511`	`19752.21541511`
`popdynm50`	`0.8220`	`0.5020`	`1.637`	`19746.54515628`	`19746.54515628`
`robot100`	`0.2140`	`0.9820`	`0.218`	`9.14268538`	`9.14268538`
`robot200`	`0.8580`	`59.6580`	`0.014`	`9.14139550`	`9.14139550`
`robot400`	`1.7430`	`52.1010`	`0.033`	`9.14102603`	`9.14102603`
`robot50`	`0.1010`	`1.0190`	`0.099`	`9.14687850`	`9.14687850`
`rocket100`	`0.6340`	`52.5200`	---	`mstat( 6) sstat(4)`	`mstat( 6) sstat(4)`
`rocket200`	`1.0570`	`137.1480`	---	`mstat( 6) sstat(4)`	`mstat( 6) sstat(4)`
`rocket400`	`7.3270`	`983.9650`	---	`-1.01283660`	`mstat( 6) sstat(4)`
`torsion100`	`2.8130`	`0.7090`	`3.968`	`-0.41823921`	`-0.41823921`
`torsion25`	`0.5190`	`0.0970`	`5.351`	`-0.41751073`	`-0.41751073`
`torsion50`	`1.1460`	`0.2700`	`4.244`	`-0.41808763`	`-0.41808763`
`torsion75`	`2.1170`	`0.4540`	`4.663`	`-0.41819940`	`-0.41819940`