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 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	-	`55`	`11`	-	-	`6`	-	`72`
CONOPT: feasible	-	-	`1`	-	-	-	-	`1`
CONOPT: infeasible	-	-	-	-	-	`3`	-	`3`
CONOPT: unbounded	-	-	`1`	-	-	-	-	`1`
CONOPT: fail	-	-	-	-	-	`4`	-	`4`
CONOPT: no data	-	-	-	-	-	-	-	`-`
total PATHNLP	`-`	`55`	`13`	`-`	`-`	`13`	`-`	`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`	`0.8500`	`0.7200`	`1.181`	`1.08982184`	`1.87252775`
`arki0016`	`796.4200`	`2.4000`	`331.842`	`867.97316601`	`867.97316601`
`arki0017`	`48.4700`	`5.2700`	`9.197`	`-121.83308010`	`-121.83308010`
`arki0018`	`1.0400`	`1.8700`	`0.556`	`0.01045662`	`0.01045662`
`arki0020`	`2.0100`	`0.4800`	`4.188`	`-41.07495436`	`-41.07495436`
`arki0021`	`1.4100`	`4.3900`	`0.321`	`-72.58210091`	`-72.58210091`
`arki0022`	`1.8000`	`9.4700`	`0.190`	`-87.09909127`	`-87.09909127`
`arki0023`	`4.2400`	`52.5500`	`0.081`	`-153.66007775`	`-153.66007775`
`catmix100`	`0.0400`	`0.2100`	`0.190`	`-0.04806939`	`-0.04806942`
`catmix200`	`0.0400`	`0.8800`	`0.045`	`-0.04805914`	`-0.04805914`
`catmix400`	`0.1300`	`2.6200`	`0.050`	`-0.04805654`	`-0.04805655`
`catmix800`	`0.4500`	`3.7000`	`0.122`	`-0.04805590`	`-0.04805590`
`chain400`	`0.1800`	`4.2900`	`0.042`	`5.06862169`	`5.06862169`
`flowchan100`	`0.0400`	`0.1200`	`0.333`	`0.00000000`	`0.00000000`
`flowchan200`	`0.0900`	`0.2600`	`0.346`	`0.00000000`	`0.00000000`
`flowchan400`	`0.3600`	`0.6900`	`0.522`	`0.00000000`	`0.00000000`
`gasoil100`	`0.2100`	`0.2800`	`0.750`	`0.00523659`	`0.00523659`
`gasoil200`	`0.3300`	`0.8900`	`0.371`	`0.00523660`	`0.00523660`
`gasoil400`	`0.7000`	`3.2200`	`0.217`	`0.00523660`	`0.00523660`
`gasoil50`	`0.1600`	`0.1000`	`1.600`	`0.00523664`	`0.00523664`
`infeas1`	`0.2500`	`1.6000`	`0.156`	`13685.59646095`	`13685.59646388`
`jbearing100`	`64.5000`	`4.6600`	`13.841`	`-0.15504196`	`-0.15504196`
`jbearing25`	`1.4200`	`0.3600`	`3.944`	`-0.15401554`	`-0.15401554`
`jbearing50`	`11.3900`	`1.2900`	`8.829`	`-0.15482422`	`-0.15482422`
`jbearing75`	`29.2200`	`2.6700`	`10.944`	`-0.15498453`	`-0.15498453`
`lnts100`	`0.2000`	`1.5700`	`0.127`	`0.55459540`	`0.55459540`
`lnts200`	`0.4900`	`43.6100`	`0.011`	`0.55457702`	`0.55457702`
`methanol100`	`0.2000`	`0.3800`	`0.526`	`0.00902229`	`0.00902229`
`methanol200`	`0.4100`	`1.1800`	`0.347`	`0.00902229`	`0.00902229`
`methanol400`	`0.9800`	`4.2200`	`0.232`	`0.00902229`	`0.00902229`
`methanol50`	`0.1000`	`0.1300`	`0.769`	`0.00902229`	`0.00902229`
`minsurf100`	`75.2100`	`5.3400`	`14.084`	`2.50694926`	`2.50694926`
`minsurf25`	`0.9300`	`0.3500`	`2.657`	`2.51948768`	`2.51948768`
`minsurf50`	`9.5700`	`1.2800`	`7.477`	`2.51488916`	`2.51488916`
`minsurf75`	`32.6000`	`2.5800`	`12.636`	`2.50568648`	`2.50568648`
`pinene100`	`0.2900`	`5.5100`	`0.053`	`19.87217015`	`19.87217015`
`pinene200`	`1.0000`	`12.2000`	`0.082`	`19.87216684`	`19.87216684`
`pinene25`	`0.1200`	`0.5400`	`0.222`	`19.87216552`	`19.87216552`
`pinene50`	`0.1300`	`0.5200`	`0.250`	`19.87216552`	`19.87216552`
`polygon25`	`0.2000`	`0.6600`	`0.303`	`-0.77914604`	`-0.77967824`
`polygon50`	`0.5100`	`46.2100`	`0.011`	`-0.78287046`	`-0.75326686`
`polygon75`	`2.6800`	`16.7200`	`0.160`	`-0.78368070`	`-0.75571564`
`popdynm100`	`2.7900`	`2.2300`	`1.251`	`19746.52860218`	`19746.52860217`
`popdynm200`	`7.9600`	`7.2800`	`1.093`	`19746.52964660`	`19746.52964660`
`popdynm25`	`0.6600`	`0.1400`	`4.714`	`19752.21541511`	`19752.21541511`
`popdynm50`	`1.4600`	`0.5400`	`2.704`	`19746.54515628`	`19746.54515628`
`robot100`	`0.1800`	`1.0500`	`0.171`	`9.14268538`	`9.14268538`
`robot200`	`0.6500`	`63.1100`	`0.010`	`9.14139550`	`9.14139550`
`robot400`	`1.5800`	`52.8800`	`0.030`	`9.14102603`	`9.14102603`
`robot50`	`0.0800`	`1.0400`	`0.077`	`9.14687850`	`9.14687850`
`rocket400`	`4.6900`	`833.7600`	`0.006`	`-1.01283660`	`-1.01283661`
`torsion100`	`23.7200`	`13.5300`	`1.753`	`-0.41823921`	`-0.41823921`
`torsion25`	`0.5400`	`0.6800`	`0.794`	`-0.41751073`	`-0.41751073`
`torsion50`	`5.1600`	`3.1200`	`1.654`	`-0.41808763`	`-0.41808763`
`torsion75`	`18.8800`	`7.3300`	`2.576`	`-0.41819940`	`-0.41819940`

CONOPT: locally optimal -- PATHNLP: feasible

Modelname	Time (CONOPT)	Time (PATHNLP)	Ratio (CONOPT/PATHNLP)	Obj (CONOPT)	Obj (PATHNLP)
`arki0004`	`0.8700`	`526.5600`	`0.002`	`323.46703883`	`17731.06323519`
`arki0011`	`4.5500`	`3610.1900`	`0.001`	`-224086.46003881`	`-224086.46003872`
`arki0015`	`0.4800`	`243.0200`	`0.002`	`-271.73572350`	`-180.93272868`
`ex8_2_2a`	`5.9800`	`1158.9300`	`0.005`	`-552.66625936`	`-197.21501795`
`ex8_2_2b`	`5.0800`	`580.0700`	`0.009`	`-552.66625909`	`133.23088057`
`ex8_2_3a`	`13.3200`	`2895.7000`	`0.005`	`-3731.07929501`	`-3106.30213581`
`ex8_2_3b`	`11.9800`	`4028.3600`	`0.003`	`-3731.07929521`	`-3114.15610847`
`ex8_2_5a`	`2.8400`	`358.8600`	`0.008`	`-830.33806707`	`-454.77410661`
`ex8_2_5b`	`2.2900`	`1234.6100`	`0.002`	`-830.33806705`	`-212.13224116`
`lnts400`	`1.1800`	`268.7000`	`0.004`	`0.55457241`	`1.33410797`
`polygon100`	`6.8100`	`441.6900`	`0.015`	`-0.78493140`	`-0.54505636`

CONOPT: locally optimal -- PATHNLP: fail

Modelname	Time (CONOPT)	Time (PATHNLP)	Ratio (CONOPT/PATHNLP)	Obj (CONOPT)	Status (PATHNLP)
`arki0012`	`902.2700`	`0.1200`	---	`-224252.44569385`	`mstat(14)sstat( 9)`
`camshape400`	`0.0500`	`12.5400`	---	`-4.27568848`	`mstat( 6)sstat( 4)`
`camshape800`	`0.1700`	`69.6400`	---	`-4.27427414`	`mstat( 6)sstat( 4)`
`elec200`	`16.3100`	`3635.2700`	---	`18439.12440042`	`mstat( 6)sstat( 3)`
`glider50`	`6.9300`	`42.8500`	---	`-1282.39972359`	`mstat( 6)sstat( 4)`
`rocket100`	`0.5800`	`30.0400`	---	`-1.01283188`	`mstat( 6)sstat( 4)`

CONOPT: feasible -- PATHNLP: feasible

Modelname	Time (CONOPT)	Time (PATHNLP)	Ratio (CONOPT/PATHNLP)	Obj (CONOPT)	Obj (PATHNLP)
`arki0003`	`7.4600`	`647.0700`	`0.012`	`118048557.91487100`	`2057363.84652296`

CONOPT: infeasible -- PATHNLP: fail

Modelname	Time (CONOPT)	Time (PATHNLP)	Ratio (CONOPT/PATHNLP)	Status (CONOPT)	Status (PATHNLP)
`arki0008`	`19.2600`	`953.9300`	---	`mstat( 5)sstat( 1)`	`mstat( 6)sstat( 4)`
`glider100`	`1.6800`	`72.2900`	---	`mstat( 5)sstat( 1)`	`mstat( 6)sstat( 4)`
`glider200`	`7.1700`	`517.4200`	---	`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`	`1.9400`	`1849.9500`	---	`mstat( 3)sstat( 1)`	`25.74674493`

CONOPT: fail -- PATHNLP: fail

Modelname	Time (CONOPT)	Time (PATHNLP)	Ratio (CONOPT/PATHNLP)	Status (CONOPT)	Status (PATHNLP)
`arki0013`	`9.8900`	`0.1100`	---	`mstat( 6)sstat( 4)`	`mstat(14)sstat( 9)`
`arki0014`	`11.1300`	`0.1300`	---	`mstat( 6)sstat( 4)`	`mstat(14)sstat( 9)`
`glider400`	`47.4200`	`1844.9700`	---	`mstat( 6)sstat( 4)`	`mstat( 6)sstat( 4)`
`rocket200`	`0.7800`	`119.6800`	---	`mstat( 6)sstat( 4)`	`mstat( 6)sstat( 4)`

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)`

PATHNLP: locally optimal:

Modelname	Time (PATHNLP)	Obj (PATHNLP)
`arki0002`	`0.7200`	`1.87252775`
`arki0016`	`2.4000`	`867.97316601`
`arki0017`	`5.2700`	`-121.83308010`
`arki0018`	`1.8700`	`0.01045662`
`arki0020`	`0.4800`	`-41.07495436`
`arki0021`	`4.3900`	`-72.58210091`
`arki0022`	`9.4700`	`-87.09909127`
`arki0023`	`52.5500`	`-153.66007775`
`catmix100`	`0.2100`	`-0.04806942`
`catmix200`	`0.8800`	`-0.04805914`
`catmix400`	`2.6200`	`-0.04805655`
`catmix800`	`3.7000`	`-0.04805590`
`chain400`	`4.2900`	`5.06862169`
`flowchan100`	`0.1200`	`0.00000000`
`flowchan200`	`0.2600`	`0.00000000`
`flowchan400`	`0.6900`	`0.00000000`
`gasoil100`	`0.2800`	`0.00523659`
`gasoil200`	`0.8900`	`0.00523660`
`gasoil400`	`3.2200`	`0.00523660`
`gasoil50`	`0.1000`	`0.00523664`
`infeas1`	`1.6000`	`13685.59646388`
`jbearing100`	`4.6600`	`-0.15504196`
`jbearing25`	`0.3600`	`-0.15401554`
`jbearing50`	`1.2900`	`-0.15482422`
`jbearing75`	`2.6700`	`-0.15498453`
`lnts100`	`1.5700`	`0.55459540`
`lnts200`	`43.6100`	`0.55457702`
`methanol100`	`0.3800`	`0.00902229`
`methanol200`	`1.1800`	`0.00902229`
`methanol400`	`4.2200`	`0.00902229`
`methanol50`	`0.1300`	`0.00902229`
`minsurf100`	`5.3400`	`2.50694926`
`minsurf25`	`0.3500`	`2.51948768`
`minsurf50`	`1.2800`	`2.51488916`
`minsurf75`	`2.5800`	`2.50568648`
`pinene100`	`5.5100`	`19.87217015`
`pinene200`	`12.2000`	`19.87216684`
`pinene25`	`0.5400`	`19.87216552`
`pinene50`	`0.5200`	`19.87216552`
`polygon25`	`0.6600`	`-0.77967824`
`polygon50`	`46.2100`	`-0.75326686`
`polygon75`	`16.7200`	`-0.75571564`
`popdynm100`	`2.2300`	`19746.52860217`
`popdynm200`	`7.2800`	`19746.52964660`
`popdynm25`	`0.1400`	`19752.21541511`
`popdynm50`	`0.5400`	`19746.54515628`
`robot100`	`1.0500`	`9.14268538`
`robot200`	`63.1100`	`9.14139550`
`robot400`	`52.8800`	`9.14102603`
`robot50`	`1.0400`	`9.14687850`
`rocket400`	`833.7600`	`-1.01283661`
`torsion100`	`13.5300`	`-0.41823921`
`torsion25`	`0.6800`	`-0.41751073`
`torsion50`	`3.1200`	`-0.41808763`
`torsion75`	`7.3300`	`-0.41819940`

PATHNLP: feasible:

Modelname	Time (PATHNLP)	Obj (PATHNLP)
`arki0003`	`647.0700`	`2057363.84652296`
`arki0004`	`526.5600`	`17731.06323519`
`arki0011`	`3610.1900`	`-224086.46003872`
`arki0015`	`243.0200`	`-180.93272868`
`ex8_2_2`	`1849.9500`	`25.74674493`
`ex8_2_2a`	`1158.9300`	`-197.21501795`
`ex8_2_2b`	`580.0700`	`133.23088057`
`ex8_2_3a`	`2895.7000`	`-3106.30213581`
`ex8_2_3b`	`4028.3600`	`-3114.15610847`
`ex8_2_5a`	`358.8600`	`-454.77410661`
`ex8_2_5b`	`1234.6100`	`-212.13224116`
`lnts400`	`268.7000`	`1.33410797`
`polygon100`	`441.6900`	`-0.54505636`

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)`
`camshape400`	`--`	`mstat( 6)sstat( 4)`
`camshape800`	`--`	`mstat( 6)sstat( 4)`
`elec200`	`--`	`mstat( 6)sstat( 3)`
`glider100`	`--`	`mstat( 6)sstat( 4)`
`glider200`	`--`	`mstat( 6)sstat( 4)`
`glider400`	`--`	`mstat( 6)sstat( 4)`
`glider50`	`--`	`mstat( 6)sstat( 4)`
`rocket100`	`--`	`mstat( 6)sstat( 4)`
`rocket200`	`--`	`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`	`0.8500`	`0.7200`	`1.181`	`1.08982184`	`1.87252775`
`arki0003`	`7.4600`	`647.0700`	`0.012`	`118048557.91487100`	`2057363.84652296`
`arki0004`	`0.8700`	`526.5600`	`0.002`	`323.46703883`	`17731.06323519`
`arki0008`	`19.2600`	`953.9300`	---	`mstat( 5) sstat(1)`	`mstat( 6) sstat(4)`
`arki0011`	`4.5500`	`3610.1900`	`0.001`	`-224086.46003881`	`-224086.46003872`
`arki0012`	`902.2700`	`0.1200`	---	`-224252.44569385`	`mstat(14) sstat(9)`
`arki0013`	`9.8900`	`0.1100`	---	`mstat( 6) sstat(4)`	`mstat(14) sstat(9)`
`arki0014`	`11.1300`	`0.1300`	---	`mstat( 6) sstat(4)`	`mstat(14) sstat(9)`
`arki0015`	`0.4800`	`243.0200`	`0.002`	`-271.73572350`	`-180.93272868`
`arki0016`	`796.4200`	`2.4000`	`331.842`	`867.97316601`	`867.97316601`
`arki0017`	`48.4700`	`5.2700`	`9.197`	`-121.83308010`	`-121.83308010`
`arki0018`	`1.0400`	`1.8700`	`0.556`	`0.01045662`	`0.01045662`
`arki0020`	`2.0100`	`0.4800`	`4.188`	`-41.07495436`	`-41.07495436`
`arki0021`	`1.4100`	`4.3900`	`0.321`	`-72.58210091`	`-72.58210091`
`arki0022`	`1.8000`	`9.4700`	`0.190`	`-87.09909127`	`-87.09909127`
`arki0023`	`4.2400`	`52.5500`	`0.081`	`-153.66007775`	`-153.66007775`
`camshape400`	`0.0500`	`12.5400`	---	`-4.27568848`	`mstat( 6) sstat(4)`
`camshape800`	`0.1700`	`69.6400`	---	`-4.27427414`	`mstat( 6) sstat(4)`
`catmix100`	`0.0400`	`0.2100`	`0.190`	`-0.04806939`	`-0.04806942`
`catmix200`	`0.0400`	`0.8800`	`0.045`	`-0.04805914`	`-0.04805914`
`catmix400`	`0.1300`	`2.6200`	`0.050`	`-0.04805654`	`-0.04805655`
`catmix800`	`0.4500`	`3.7000`	`0.122`	`-0.04805590`	`-0.04805590`
`chain400`	`0.1800`	`4.2900`	`0.042`	`5.06862169`	`5.06862169`
`elec200`	`16.3100`	`3635.2700`	---	`18439.12440042`	`mstat( 6) sstat(3)`
`ex8_2_2`	`1.9400`	`1849.9500`	---	`mstat( 3) sstat(1)`	`25.74674493`
`ex8_2_2a`	`5.9800`	`1158.9300`	`0.005`	`-552.66625936`	`-197.21501795`
`ex8_2_2b`	`5.0800`	`580.0700`	`0.009`	`-552.66625909`	`133.23088057`
`ex8_2_3a`	`13.3200`	`2895.7000`	`0.005`	`-3731.07929501`	`-3106.30213581`
`ex8_2_3b`	`11.9800`	`4028.3600`	`0.003`	`-3731.07929521`	`-3114.15610847`
`ex8_2_5a`	`2.8400`	`358.8600`	`0.008`	`-830.33806707`	`-454.77410661`
`ex8_2_5b`	`2.2900`	`1234.6100`	`0.002`	`-830.33806705`	`-212.13224116`
`flowchan100`	`0.0400`	`0.1200`	`0.333`	`0.00000000`	`0.00000000`
`flowchan200`	`0.0900`	`0.2600`	`0.346`	`0.00000000`	`0.00000000`
`flowchan400`	`0.3600`	`0.6900`	`0.522`	`0.00000000`	`0.00000000`
`gasoil100`	`0.2100`	`0.2800`	`0.750`	`0.00523659`	`0.00523659`
`gasoil200`	`0.3300`	`0.8900`	`0.371`	`0.00523660`	`0.00523660`
`gasoil400`	`0.7000`	`3.2200`	`0.217`	`0.00523660`	`0.00523660`
`gasoil50`	`0.1600`	`0.1000`	`1.600`	`0.00523664`	`0.00523664`
`glider100`	`1.6800`	`72.2900`	---	`mstat( 5) sstat(1)`	`mstat( 6) sstat(4)`
`glider200`	`7.1700`	`517.4200`	---	`mstat( 5) sstat(1)`	`mstat( 6) sstat(4)`
`glider400`	`47.4200`	`1844.9700`	---	`mstat( 6) sstat(4)`	`mstat( 6) sstat(4)`
`glider50`	`6.9300`	`42.8500`	---	`-1282.39972359`	`mstat( 6) sstat(4)`
`infeas1 (max)`	`0.2500`	`1.6000`	`0.156`	`13685.59646095`	`13685.59646388`
`jbearing100`	`64.5000`	`4.6600`	`13.841`	`-0.15504196`	`-0.15504196`
`jbearing25`	`1.4200`	`0.3600`	`3.944`	`-0.15401554`	`-0.15401554`
`jbearing50`	`11.3900`	`1.2900`	`8.829`	`-0.15482422`	`-0.15482422`
`jbearing75`	`29.2200`	`2.6700`	`10.944`	`-0.15498453`	`-0.15498453`
`lnts100`	`0.2000`	`1.5700`	`0.127`	`0.55459540`	`0.55459540`
`lnts200`	`0.4900`	`43.6100`	`0.011`	`0.55457702`	`0.55457702`
`lnts400`	`1.1800`	`268.7000`	`0.004`	`0.55457241`	`1.33410797`
`methanol100`	`0.2000`	`0.3800`	`0.526`	`0.00902229`	`0.00902229`
`methanol200`	`0.4100`	`1.1800`	`0.347`	`0.00902229`	`0.00902229`
`methanol400`	`0.9800`	`4.2200`	`0.232`	`0.00902229`	`0.00902229`
`methanol50`	`0.1000`	`0.1300`	`0.769`	`0.00902229`	`0.00902229`
`minsurf100`	`75.2100`	`5.3400`	`14.084`	`2.50694926`	`2.50694926`
`minsurf25`	`0.9300`	`0.3500`	`2.657`	`2.51948768`	`2.51948768`
`minsurf50`	`9.5700`	`1.2800`	`7.477`	`2.51488916`	`2.51488916`
`minsurf75`	`32.6000`	`2.5800`	`12.636`	`2.50568648`	`2.50568648`
`pinene100`	`0.2900`	`5.5100`	`0.053`	`19.87217015`	`19.87217015`
`pinene200`	`1.0000`	`12.2000`	`0.082`	`19.87216684`	`19.87216684`
`pinene25`	`0.1200`	`0.5400`	`0.222`	`19.87216552`	`19.87216552`
`pinene50`	`0.1300`	`0.5200`	`0.250`	`19.87216552`	`19.87216552`
`polygon100`	`6.8100`	`441.6900`	`0.015`	`-0.78493140`	`-0.54505636`
`polygon25`	`0.2000`	`0.6600`	`0.303`	`-0.77914604`	`-0.77967824`
`polygon50`	`0.5100`	`46.2100`	`0.011`	`-0.78287046`	`-0.75326686`
`polygon75`	`2.6800`	`16.7200`	`0.160`	`-0.78368070`	`-0.75571564`
`popdynm100`	`2.7900`	`2.2300`	`1.251`	`19746.52860218`	`19746.52860217`
`popdynm200`	`7.9600`	`7.2800`	`1.093`	`19746.52964660`	`19746.52964660`
`popdynm25`	`0.6600`	`0.1400`	`4.714`	`19752.21541511`	`19752.21541511`
`popdynm50`	`1.4600`	`0.5400`	`2.704`	`19746.54515628`	`19746.54515628`
`robot100`	`0.1800`	`1.0500`	`0.171`	`9.14268538`	`9.14268538`
`robot200`	`0.6500`	`63.1100`	`0.010`	`9.14139550`	`9.14139550`
`robot400`	`1.5800`	`52.8800`	`0.030`	`9.14102603`	`9.14102603`
`robot50`	`0.0800`	`1.0400`	`0.077`	`9.14687850`	`9.14687850`
`rocket100`	`0.5800`	`30.0400`	---	`-1.01283188`	`mstat( 6) sstat(4)`
`rocket200`	`0.7800`	`119.6800`	---	`mstat( 6) sstat(4)`	`mstat( 6) sstat(4)`
`rocket400`	`4.6900`	`833.7600`	`0.006`	`-1.01283660`	`-1.01283661`
`torsion100`	`23.7200`	`13.5300`	`1.753`	`-0.41823921`	`-0.41823921`
`torsion25`	`0.5400`	`0.6800`	`0.794`	`-0.41751073`	`-0.41751073`
`torsion50`	`5.1600`	`3.1200`	`1.654`	`-0.41808763`	`-0.41808763`
`torsion75`	`18.8800`	`7.3300`	`2.576`	`-0.41819940`	`-0.41819940`