Solver Square Comparison

Solver Square Comparison: Considers all models.

Results created on 11/20/09 15:35:09 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 SNOPT 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:	SNOPT-1.trc
Solvers used :	CONOPT
	SNOPT
Modeltype(s)	`NLP`

	SNOPT: optimal	SNOPT: locally optimal	SNOPT: feasible	SNOPT: infeasible	SNOPT: unbounded	SNOPT: fail	SNOPT: no data	total CONOPT
CONOPT: optimal	-	-	-	-	-	-	-	`-`
CONOPT: locally optimal	-	`66`	`4`	`1`	-	`1`	-	`72`
CONOPT: feasible	-	`1`	-	-	-	-	-	`1`
CONOPT: infeasible	-	-	-	`3`	-	-	-	`3`
CONOPT: unbounded	-	-	-	-	-	`1`	-	`1`
CONOPT: fail	-	`3`	`1`	-	-	-	-	`4`
CONOPT: no data	-	-	-	-	-	-	-	`-`
total SNOPT	`-`	`70`	`5`	`4`	`-`	`2`	`-`	`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 -- SNOPT: locally optimal

Modelname	Time (CONOPT)	Time (SNOPT)	Ratio (CONOPT/SNOPT)	Obj (CONOPT)	Obj (SNOPT)
`arki0002`	`0.8500`	`154.4600`	`0.006`	`1.08982184`	`1.09249984`
`arki0004`	`0.8700`	`0.4100`	`2.122`	`323.46703883`	`323.46703883`
`arki0011`	`4.5500`	`401.7400`	`0.011`	`-224086.46003881`	`-224086.45991302`
`arki0015`	`0.4800`	`3.6100`	`0.133`	`-271.73572350`	`-272.29977820`
`arki0020`	`2.0100`	`22.2700`	`0.090`	`-41.07495436`	`-41.07495436`
`arki0021`	`1.4100`	`89.1400`	`0.016`	`-72.58210091`	`-72.58210091`
`arki0022`	`1.8000`	`110.2400`	`0.016`	`-87.09909127`	`-87.09909127`
`camshape400`	`0.0500`	`0.1100`	`0.455`	`-4.27568848`	`-4.27568692`
`camshape800`	`0.1700`	`0.4300`	`0.395`	`-4.27427414`	`-4.27427301`
`catmix100`	`0.0400`	`0.1600`	`0.250`	`-0.04806939`	`-0.04806940`
`catmix200`	`0.0400`	`0.7000`	`0.057`	`-0.04805914`	`-0.04805914`
`catmix400`	`0.1300`	`2.4800`	`0.052`	`-0.04805654`	`-0.04805655`
`catmix800`	`0.4500`	`10.7000`	`0.042`	`-0.04805590`	`-0.04805590`
`chain400`	`0.1800`	`7.0200`	`0.026`	`5.06862169`	`5.06862169`
`elec200`	`16.3100`	`11.7800`	`1.385`	`18439.12440042`	`18438.99267601`
`ex8_2_2a`	`5.9800`	`92.3800`	`0.065`	`-552.66625936`	`-552.65761566`
`ex8_2_2b`	`5.0800`	`6.7000`	`0.758`	`-552.66625909`	`-551.76977942`
`ex8_2_3a`	`13.3200`	`48.3600`	`0.275`	`-3731.07929501`	`-3731.07809337`
`ex8_2_3b`	`11.9800`	`22.1800`	`0.540`	`-3731.07929521`	`-3730.72924954`
`ex8_2_5a`	`2.8400`	`184.5500`	`0.015`	`-830.33806707`	`-830.33802832`
`ex8_2_5b`	`2.2900`	`6.6800`	`0.343`	`-830.33806705`	`-830.07940808`
`flowchan100`	`0.0400`	`0.3200`	`0.125`	`0.00000000`	`0.00000000`
`flowchan200`	`0.0900`	`1.0600`	`0.085`	`0.00000000`	`0.00000000`
`flowchan400`	`0.3600`	`3.2800`	`0.110`	`0.00000000`	`0.00000000`
`gasoil100`	`0.2100`	`0.4900`	`0.429`	`0.00523659`	`0.00523659`
`gasoil200`	`0.3300`	`1.4800`	`0.223`	`0.00523660`	`0.00523660`
`gasoil400`	`0.7000`	`6.6200`	`0.106`	`0.00523660`	`0.00523660`
`gasoil50`	`0.1600`	`0.2200`	`0.727`	`0.00523664`	`0.00523664`
`glider50`	`6.9300`	`55.3500`	`0.125`	`-1282.39972359`	`-1286.97737315`
`jbearing100`	`64.5000`	`40.2300`	`1.603`	`-0.15504196`	`-0.15504196`
`jbearing25`	`1.4200`	`6.6600`	`0.213`	`-0.15401554`	`-0.15401554`
`jbearing50`	`11.3900`	`29.9100`	`0.381`	`-0.15482422`	`-0.15482422`
`jbearing75`	`29.2200`	`26.7100`	`1.094`	`-0.15498453`	`-0.15498453`
`lnts100`	`0.2000`	`0.3600`	`0.556`	`0.55459540`	`0.55459540`
`lnts200`	`0.4900`	`1.4300`	`0.343`	`0.55457702`	`0.55457702`
`lnts400`	`1.1800`	`6.3600`	`0.186`	`0.55457241`	`0.55457241`
`methanol100`	`0.2000`	`0.8500`	`0.235`	`0.00902229`	`0.00902229`
`methanol200`	`0.4100`	`2.4800`	`0.165`	`0.00902229`	`0.00902229`
`methanol400`	`0.9800`	`8.4000`	`0.117`	`0.00902229`	`0.00902229`
`methanol50`	`0.1000`	`0.3500`	`0.286`	`0.00902229`	`0.00902229`
`minsurf100`	`75.2100`	`295.6700`	`0.254`	`2.50694926`	`2.50694926`
`minsurf25`	`0.9300`	`5.4600`	`0.170`	`2.51948768`	`2.51948768`
`minsurf50`	`9.5700`	`67.8900`	`0.141`	`2.51488916`	`2.51488916`
`minsurf75`	`32.6000`	`152.5700`	`0.214`	`2.50568648`	`2.50568648`
`pinene100`	`0.2900`	`2.3000`	`0.126`	`19.87217015`	`19.87217014`
`pinene200`	`1.0000`	`10.5100`	`0.095`	`19.87216684`	`19.87216684`
`pinene25`	`0.1200`	`1.0000`	`0.120`	`19.87216552`	`19.87216552`
`pinene50`	`0.1300`	`0.9800`	`0.133`	`19.87216552`	`19.87216552`
`polygon100`	`6.8100`	`20.7200`	`0.329`	`-0.78493140`	`-0.78503127`
`polygon25`	`0.2000`	`0.0300`	`6.667`	`-0.77914604`	`-0.77973670`
`polygon50`	`0.5100`	`1.5000`	`0.340`	`-0.78287046`	`-0.78401305`
`polygon75`	`2.6800`	`5.1400`	`0.521`	`-0.78368070`	`-0.78478846`
`popdynm100`	`2.7900`	`1.9300`	`1.446`	`19746.52860218`	`19746.52860217`
`popdynm200`	`7.9600`	`5.9600`	`1.336`	`19746.52964660`	`19746.52964660`
`popdynm25`	`0.6600`	`0.3100`	`2.129`	`19752.21541511`	`19752.21541511`
`popdynm50`	`1.4600`	`1.0300`	`1.417`	`19746.54515628`	`19746.54515628`
`robot100`	`0.1800`	`0.8200`	`0.220`	`9.14268538`	`9.14268538`
`robot200`	`0.6500`	`15.2600`	`0.043`	`9.14139550`	`9.14139550`
`robot400`	`1.5800`	`44.6300`	`0.035`	`9.14102603`	`9.14102603`
`robot50`	`0.0800`	`0.1600`	`0.500`	`9.14687850`	`9.14687850`
`rocket100`	`0.5800`	`0.6700`	`0.866`	`-1.01283188`	`-1.01283202`
`rocket400`	`4.6900`	`9.2400`	`0.508`	`-1.01283660`	`-1.01283661`
`torsion100`	`23.7200`	`19.1900`	`1.236`	`-0.41823921`	`-0.41823921`
`torsion25`	`0.5400`	`1.4500`	`0.372`	`-0.41751073`	`-0.41751073`
`torsion50`	`5.1600`	`12.9000`	`0.400`	`-0.41808763`	`-0.41808763`
`torsion75`	`18.8800`	`12.3000`	`1.535`	`-0.41819940`	`-0.41819940`

CONOPT: locally optimal -- SNOPT: feasible

Modelname	Time (CONOPT)	Time (SNOPT)	Ratio (CONOPT/SNOPT)	Obj (CONOPT)	Obj (SNOPT)
`arki0012`	`902.2700`	`3600.2200`	`0.251`	`-224252.44569385`	`-224171.55016260`
`arki0017`	`48.4700`	`1680.0100`	`0.029`	`-121.83308010`	`-121.83308010`
`arki0018`	`1.0400`	`40.2800`	`0.026`	`0.01045662`	`0.01197639`
`arki0023`	`4.2400`	`81.0700`	`0.052`	`-153.66007775`	`-153.41732339`

CONOPT: locally optimal -- SNOPT: infeasible

Modelname	Time (CONOPT)	Time (SNOPT)	Ratio (CONOPT/SNOPT)	Obj (CONOPT)	Status (SNOPT)
`infeas1`	`0.2500`	`0.0200`	---	`13685.59646095`	`mstat( 4)sstat( 1)`

CONOPT: locally optimal -- SNOPT: fail

Modelname	Time (CONOPT)	Time (SNOPT)	Ratio (CONOPT/SNOPT)	Obj (CONOPT)	Status (SNOPT)
`arki0016`	`796.4200`	`NA`	---	`867.97316601`	`mstat(13)sstat(13)`

CONOPT: feasible -- SNOPT: locally optimal

Modelname	Time (CONOPT)	Time (SNOPT)	Ratio (CONOPT/SNOPT)	Obj (CONOPT)	Obj (SNOPT)
`arki0003`	`7.4600`	`1.4500`	`5.145`	`118048557.91487100`	`3795.20606780`

CONOPT: infeasible -- SNOPT: infeasible

Modelname	Time (CONOPT)	Time (SNOPT)	Ratio (CONOPT/SNOPT)	Status (CONOPT)	Status (SNOPT)
`arki0008`	`19.2600`	`7.4400`	---	`mstat( 5)sstat( 1)`	`mstat( 5)sstat( 1)`
`glider100`	`1.6800`	`1.2200`	---	`mstat( 5)sstat( 1)`	`mstat( 5)sstat( 1)`
`glider200`	`7.1700`	`1.8000`	---	`mstat( 5)sstat( 1)`	`mstat( 5)sstat( 1)`

CONOPT: unbounded -- SNOPT: fail

Modelname	Time (CONOPT)	Time (SNOPT)	Ratio (CONOPT/SNOPT)	Status (CONOPT)	Status (SNOPT)
`ex8_2_2`	`1.9400`	`NA`	---	`mstat( 3)sstat( 1)`	`mstat(13)sstat(13)`

CONOPT: fail -- SNOPT: locally optimal

Modelname	Time (CONOPT)	Time (SNOPT)	Ratio (CONOPT/SNOPT)	Status (CONOPT)	Obj (SNOPT)
`arki0013`	`9.8900`	`1709.7900`	---	`mstat( 6)sstat( 4)`	`-224253.08921947`
`arki0014`	`11.1300`	`3504.7300`	---	`mstat( 6)sstat( 4)`	`-223977.09382739`
`rocket200`	`0.7800`	`2.9800`	---	`mstat( 6)sstat( 4)`	`-1.01283569`

CONOPT: fail -- SNOPT: feasible

Modelname	Time (CONOPT)	Time (SNOPT)	Ratio (CONOPT/SNOPT)	Status (CONOPT)	Obj (SNOPT)
`glider400`	`47.4200`	`3600.0000`	---	`mstat( 6)sstat( 4)`	`-254.82412037`

CONOPT: locally optimal:

Modelname	Time (CONOPT)	Obj (CONOPT)
`arki0002`	`0.8500`	`1.08982184`
`arki0004`	`0.8700`	`323.46703883`
`arki0011`	`4.5500`	`-224086.46003881`
`arki0012`	`902.2700`	`-224252.44569385`
`arki0015`	`0.4800`	`-271.73572350`
`arki0016`	`796.4200`	`867.97316601`
`arki0017`	`48.4700`	`-121.83308010`
`arki0018`	`1.0400`	`0.01045662`
`arki0020`	`2.0100`	`-41.07495436`
`arki0021`	`1.4100`	`-72.58210091`
`arki0022`	`1.8000`	`-87.09909127`
`arki0023`	`4.2400`	`-153.66007775`
`camshape400`	`0.0500`	`-4.27568848`
`camshape800`	`0.1700`	`-4.27427414`
`catmix100`	`0.0400`	`-0.04806939`
`catmix200`	`0.0400`	`-0.04805914`
`catmix400`	`0.1300`	`-0.04805654`
`catmix800`	`0.4500`	`-0.04805590`
`chain400`	`0.1800`	`5.06862169`
`elec200`	`16.3100`	`18439.12440042`
`ex8_2_2a`	`5.9800`	`-552.66625936`
`ex8_2_2b`	`5.0800`	`-552.66625909`
`ex8_2_3a`	`13.3200`	`-3731.07929501`
`ex8_2_3b`	`11.9800`	`-3731.07929521`
`ex8_2_5a`	`2.8400`	`-830.33806707`
`ex8_2_5b`	`2.2900`	`-830.33806705`
`flowchan100`	`0.0400`	`0.00000000`
`flowchan200`	`0.0900`	`0.00000000`
`flowchan400`	`0.3600`	`0.00000000`
`gasoil100`	`0.2100`	`0.00523659`
`gasoil200`	`0.3300`	`0.00523660`
`gasoil400`	`0.7000`	`0.00523660`
`gasoil50`	`0.1600`	`0.00523664`
`glider50`	`6.9300`	`-1282.39972359`
`infeas1`	`0.2500`	`13685.59646095`
`jbearing100`	`64.5000`	`-0.15504196`
`jbearing25`	`1.4200`	`-0.15401554`
`jbearing50`	`11.3900`	`-0.15482422`
`jbearing75`	`29.2200`	`-0.15498453`
`lnts100`	`0.2000`	`0.55459540`
`lnts200`	`0.4900`	`0.55457702`
`lnts400`	`1.1800`	`0.55457241`
`methanol100`	`0.2000`	`0.00902229`
`methanol200`	`0.4100`	`0.00902229`
`methanol400`	`0.9800`	`0.00902229`
`methanol50`	`0.1000`	`0.00902229`
`minsurf100`	`75.2100`	`2.50694926`
`minsurf25`	`0.9300`	`2.51948768`
`minsurf50`	`9.5700`	`2.51488916`
`minsurf75`	`32.6000`	`2.50568648`
`pinene100`	`0.2900`	`19.87217015`
`pinene200`	`1.0000`	`19.87216684`
`pinene25`	`0.1200`	`19.87216552`
`pinene50`	`0.1300`	`19.87216552`
`polygon100`	`6.8100`	`-0.78493140`
`polygon25`	`0.2000`	`-0.77914604`
`polygon50`	`0.5100`	`-0.78287046`
`polygon75`	`2.6800`	`-0.78368070`
`popdynm100`	`2.7900`	`19746.52860218`
`popdynm200`	`7.9600`	`19746.52964660`
`popdynm25`	`0.6600`	`19752.21541511`
`popdynm50`	`1.4600`	`19746.54515628`
`robot100`	`0.1800`	`9.14268538`
`robot200`	`0.6500`	`9.14139550`
`robot400`	`1.5800`	`9.14102603`
`robot50`	`0.0800`	`9.14687850`
`rocket100`	`0.5800`	`-1.01283188`
`rocket400`	`4.6900`	`-1.01283660`
`torsion100`	`23.7200`	`-0.41823921`
`torsion25`	`0.5400`	`-0.41751073`
`torsion50`	`5.1600`	`-0.41808763`
`torsion75`	`18.8800`	`-0.41819940`

CONOPT: feasible:

Modelname	Time (CONOPT)	Obj (CONOPT)
`arki0003`	`7.4600`	`118048557.91487100`

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`	`1.9400`	`mstat( 3) sstat( 1)`

CONOPT: fail:

Modelname	Time (CONOPT)	Status (CONOPT)
`arki0013`	`--`	`mstat( 6) sstat( 4)`
`arki0014`	`--`	`mstat( 6) sstat( 4)`
`glider400`	`--`	`mstat( 6) sstat( 4)`
`rocket200`	`--`	`mstat( 6) sstat( 4)`

SNOPT: locally optimal:

Modelname	Time (SNOPT)	Obj (SNOPT)
`arki0002`	`154.4600`	`1.09249984`
`arki0003`	`1.4500`	`3795.20606780`
`arki0004`	`0.4100`	`323.46703883`
`arki0011`	`401.7400`	`-224086.45991302`
`arki0013`	`1709.7900`	`-224253.08921947`
`arki0014`	`3504.7300`	`-223977.09382739`
`arki0015`	`3.6100`	`-272.29977820`
`arki0020`	`22.2700`	`-41.07495436`
`arki0021`	`89.1400`	`-72.58210091`
`arki0022`	`110.2400`	`-87.09909127`
`camshape400`	`0.1100`	`-4.27568692`
`camshape800`	`0.4300`	`-4.27427301`
`catmix100`	`0.1600`	`-0.04806940`
`catmix200`	`0.7000`	`-0.04805914`
`catmix400`	`2.4800`	`-0.04805655`
`catmix800`	`10.7000`	`-0.04805590`
`chain400`	`7.0200`	`5.06862169`
`elec200`	`11.7800`	`18438.99267601`
`ex8_2_2a`	`92.3800`	`-552.65761566`
`ex8_2_2b`	`6.7000`	`-551.76977942`
`ex8_2_3a`	`48.3600`	`-3731.07809337`
`ex8_2_3b`	`22.1800`	`-3730.72924954`
`ex8_2_5a`	`184.5500`	`-830.33802832`
`ex8_2_5b`	`6.6800`	`-830.07940808`
`flowchan100`	`0.3200`	`0.00000000`
`flowchan200`	`1.0600`	`0.00000000`
`flowchan400`	`3.2800`	`0.00000000`
`gasoil100`	`0.4900`	`0.00523659`
`gasoil200`	`1.4800`	`0.00523660`
`gasoil400`	`6.6200`	`0.00523660`
`gasoil50`	`0.2200`	`0.00523664`
`glider50`	`55.3500`	`-1286.97737315`
`jbearing100`	`40.2300`	`-0.15504196`
`jbearing25`	`6.6600`	`-0.15401554`
`jbearing50`	`29.9100`	`-0.15482422`
`jbearing75`	`26.7100`	`-0.15498453`
`lnts100`	`0.3600`	`0.55459540`
`lnts200`	`1.4300`	`0.55457702`
`lnts400`	`6.3600`	`0.55457241`
`methanol100`	`0.8500`	`0.00902229`
`methanol200`	`2.4800`	`0.00902229`
`methanol400`	`8.4000`	`0.00902229`
`methanol50`	`0.3500`	`0.00902229`
`minsurf100`	`295.6700`	`2.50694926`
`minsurf25`	`5.4600`	`2.51948768`
`minsurf50`	`67.8900`	`2.51488916`
`minsurf75`	`152.5700`	`2.50568648`
`pinene100`	`2.3000`	`19.87217014`
`pinene200`	`10.5100`	`19.87216684`
`pinene25`	`1.0000`	`19.87216552`
`pinene50`	`0.9800`	`19.87216552`
`polygon100`	`20.7200`	`-0.78503127`
`polygon25`	`0.0300`	`-0.77973670`
`polygon50`	`1.5000`	`-0.78401305`
`polygon75`	`5.1400`	`-0.78478846`
`popdynm100`	`1.9300`	`19746.52860217`
`popdynm200`	`5.9600`	`19746.52964660`
`popdynm25`	`0.3100`	`19752.21541511`
`popdynm50`	`1.0300`	`19746.54515628`
`robot100`	`0.8200`	`9.14268538`
`robot200`	`15.2600`	`9.14139550`
`robot400`	`44.6300`	`9.14102603`
`robot50`	`0.1600`	`9.14687850`
`rocket100`	`0.6700`	`-1.01283202`
`rocket200`	`2.9800`	`-1.01283569`
`rocket400`	`9.2400`	`-1.01283661`
`torsion100`	`19.1900`	`-0.41823921`
`torsion25`	`1.4500`	`-0.41751073`
`torsion50`	`12.9000`	`-0.41808763`
`torsion75`	`12.3000`	`-0.41819940`

SNOPT: feasible:

Modelname	Time (SNOPT)	Obj (SNOPT)
`arki0012`	`3600.2200`	`-224171.55016260`
`arki0017`	`1680.0100`	`-121.83308010`
`arki0018`	`40.2800`	`0.01197639`
`arki0023`	`81.0700`	`-153.41732339`
`glider400`	`3600.0000`	`-254.82412037`

SNOPT: infeasible:

Modelname	Time (SNOPT)	Status (SNOPT)
`arki0008`	`--`	`mstat( 5)sstat( 1)`
`glider100`	`--`	`mstat( 5)sstat( 1)`
`glider200`	`--`	`mstat( 5)sstat( 1)`
`infeas1`	`--`	`mstat( 4)sstat( 1)`

SNOPT: fail:

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

CONOPT: all -- SNOPT: all

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

Modelname	Time (CONOPT)	Time (SNOPT)	Ratio (CONOPT/ SNOPT)	Obj (CONOPT)	Obj (SNOPT)
`arki0002`	`0.8500`	`154.4600`	`0.006`	`1.08982184`	`1.09249984`
`arki0003`	`7.4600`	`1.4500`	`5.145`	`118048557.91487100`	`3795.20606780`
`arki0004`	`0.8700`	`0.4100`	`2.122`	`323.46703883`	`323.46703883`
`arki0008`	`19.2600`	`7.4400`	---	`mstat( 5) sstat(1)`	`mstat( 5) sstat(1)`
`arki0011`	`4.5500`	`401.7400`	`0.011`	`-224086.46003881`	`-224086.45991302`
`arki0012`	`902.2700`	`3600.2200`	`0.251`	`-224252.44569385`	`-224171.55016260`
`arki0013`	`9.8900`	`1709.7900`	---	`mstat( 6) sstat(4)`	`-224253.08921947`
`arki0014`	`11.1300`	`3504.7300`	---	`mstat( 6) sstat(4)`	`-223977.09382739`
`arki0015`	`0.4800`	`3.6100`	`0.133`	`-271.73572350`	`-272.29977820`
`arki0016`	`796.4200`	`NA`	---	`867.97316601`	`mstat(13) sstat(13)`
`arki0017`	`48.4700`	`1680.0100`	`0.029`	`-121.83308010`	`-121.83308010`
`arki0018`	`1.0400`	`40.2800`	`0.026`	`0.01045662`	`0.01197639`
`arki0020`	`2.0100`	`22.2700`	`0.090`	`-41.07495436`	`-41.07495436`
`arki0021`	`1.4100`	`89.1400`	`0.016`	`-72.58210091`	`-72.58210091`
`arki0022`	`1.8000`	`110.2400`	`0.016`	`-87.09909127`	`-87.09909127`
`arki0023`	`4.2400`	`81.0700`	`0.052`	`-153.66007775`	`-153.41732339`
`camshape400`	`0.0500`	`0.1100`	`0.455`	`-4.27568848`	`-4.27568692`
`camshape800`	`0.1700`	`0.4300`	`0.395`	`-4.27427414`	`-4.27427301`
`catmix100`	`0.0400`	`0.1600`	`0.250`	`-0.04806939`	`-0.04806940`
`catmix200`	`0.0400`	`0.7000`	`0.057`	`-0.04805914`	`-0.04805914`
`catmix400`	`0.1300`	`2.4800`	`0.052`	`-0.04805654`	`-0.04805655`
`catmix800`	`0.4500`	`10.7000`	`0.042`	`-0.04805590`	`-0.04805590`
`chain400`	`0.1800`	`7.0200`	`0.026`	`5.06862169`	`5.06862169`
`elec200`	`16.3100`	`11.7800`	`1.385`	`18439.12440042`	`18438.99267601`
`ex8_2_2`	`1.9400`	`NA`	---	`mstat( 3) sstat(1)`	`mstat(13) sstat(13)`
`ex8_2_2a`	`5.9800`	`92.3800`	`0.065`	`-552.66625936`	`-552.65761566`
`ex8_2_2b`	`5.0800`	`6.7000`	`0.758`	`-552.66625909`	`-551.76977942`
`ex8_2_3a`	`13.3200`	`48.3600`	`0.275`	`-3731.07929501`	`-3731.07809337`
`ex8_2_3b`	`11.9800`	`22.1800`	`0.540`	`-3731.07929521`	`-3730.72924954`
`ex8_2_5a`	`2.8400`	`184.5500`	`0.015`	`-830.33806707`	`-830.33802832`
`ex8_2_5b`	`2.2900`	`6.6800`	`0.343`	`-830.33806705`	`-830.07940808`
`flowchan100`	`0.0400`	`0.3200`	`0.125`	`0.00000000`	`0.00000000`
`flowchan200`	`0.0900`	`1.0600`	`0.085`	`0.00000000`	`0.00000000`
`flowchan400`	`0.3600`	`3.2800`	`0.110`	`0.00000000`	`0.00000000`
`gasoil100`	`0.2100`	`0.4900`	`0.429`	`0.00523659`	`0.00523659`
`gasoil200`	`0.3300`	`1.4800`	`0.223`	`0.00523660`	`0.00523660`
`gasoil400`	`0.7000`	`6.6200`	`0.106`	`0.00523660`	`0.00523660`
`gasoil50`	`0.1600`	`0.2200`	`0.727`	`0.00523664`	`0.00523664`
`glider100`	`1.6800`	`1.2200`	---	`mstat( 5) sstat(1)`	`mstat( 5) sstat(1)`
`glider200`	`7.1700`	`1.8000`	---	`mstat( 5) sstat(1)`	`mstat( 5) sstat(1)`
`glider400`	`47.4200`	`3600.0000`	---	`mstat( 6) sstat(4)`	`-254.82412037`
`glider50`	`6.9300`	`55.3500`	`0.125`	`-1282.39972359`	`-1286.97737315`
`infeas1 (max)`	`0.2500`	`0.0200`	---	`13685.59646095`	`mstat( 4) sstat(1)`
`jbearing100`	`64.5000`	`40.2300`	`1.603`	`-0.15504196`	`-0.15504196`
`jbearing25`	`1.4200`	`6.6600`	`0.213`	`-0.15401554`	`-0.15401554`
`jbearing50`	`11.3900`	`29.9100`	`0.381`	`-0.15482422`	`-0.15482422`
`jbearing75`	`29.2200`	`26.7100`	`1.094`	`-0.15498453`	`-0.15498453`
`lnts100`	`0.2000`	`0.3600`	`0.556`	`0.55459540`	`0.55459540`
`lnts200`	`0.4900`	`1.4300`	`0.343`	`0.55457702`	`0.55457702`
`lnts400`	`1.1800`	`6.3600`	`0.186`	`0.55457241`	`0.55457241`
`methanol100`	`0.2000`	`0.8500`	`0.235`	`0.00902229`	`0.00902229`
`methanol200`	`0.4100`	`2.4800`	`0.165`	`0.00902229`	`0.00902229`
`methanol400`	`0.9800`	`8.4000`	`0.117`	`0.00902229`	`0.00902229`
`methanol50`	`0.1000`	`0.3500`	`0.286`	`0.00902229`	`0.00902229`
`minsurf100`	`75.2100`	`295.6700`	`0.254`	`2.50694926`	`2.50694926`
`minsurf25`	`0.9300`	`5.4600`	`0.170`	`2.51948768`	`2.51948768`
`minsurf50`	`9.5700`	`67.8900`	`0.141`	`2.51488916`	`2.51488916`
`minsurf75`	`32.6000`	`152.5700`	`0.214`	`2.50568648`	`2.50568648`
`pinene100`	`0.2900`	`2.3000`	`0.126`	`19.87217015`	`19.87217014`
`pinene200`	`1.0000`	`10.5100`	`0.095`	`19.87216684`	`19.87216684`
`pinene25`	`0.1200`	`1.0000`	`0.120`	`19.87216552`	`19.87216552`
`pinene50`	`0.1300`	`0.9800`	`0.133`	`19.87216552`	`19.87216552`
`polygon100`	`6.8100`	`20.7200`	`0.329`	`-0.78493140`	`-0.78503127`
`polygon25`	`0.2000`	`0.0300`	`6.667`	`-0.77914604`	`-0.77973670`
`polygon50`	`0.5100`	`1.5000`	`0.340`	`-0.78287046`	`-0.78401305`
`polygon75`	`2.6800`	`5.1400`	`0.521`	`-0.78368070`	`-0.78478846`
`popdynm100`	`2.7900`	`1.9300`	`1.446`	`19746.52860218`	`19746.52860217`
`popdynm200`	`7.9600`	`5.9600`	`1.336`	`19746.52964660`	`19746.52964660`
`popdynm25`	`0.6600`	`0.3100`	`2.129`	`19752.21541511`	`19752.21541511`
`popdynm50`	`1.4600`	`1.0300`	`1.417`	`19746.54515628`	`19746.54515628`
`robot100`	`0.1800`	`0.8200`	`0.220`	`9.14268538`	`9.14268538`
`robot200`	`0.6500`	`15.2600`	`0.043`	`9.14139550`	`9.14139550`
`robot400`	`1.5800`	`44.6300`	`0.035`	`9.14102603`	`9.14102603`
`robot50`	`0.0800`	`0.1600`	`0.500`	`9.14687850`	`9.14687850`
`rocket100`	`0.5800`	`0.6700`	`0.866`	`-1.01283188`	`-1.01283202`
`rocket200`	`0.7800`	`2.9800`	---	`mstat( 6) sstat(4)`	`-1.01283569`
`rocket400`	`4.6900`	`9.2400`	`0.508`	`-1.01283660`	`-1.01283661`
`torsion100`	`23.7200`	`19.1900`	`1.236`	`-0.41823921`	`-0.41823921`
`torsion25`	`0.5400`	`1.4500`	`0.372`	`-0.41751073`	`-0.41751073`
`torsion50`	`5.1600`	`12.9000`	`0.400`	`-0.41808763`	`-0.41808763`
`torsion75`	`18.8800`	`12.3000`	`1.535`	`-0.41819940`	`-0.41819940`