Solver Square Comparison

Solver Square Comparison: Considers all models.

Results created on 03/04/11 12:14:17 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-MUMPS is represented on the left (rows) and solver CONOPT 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-2.trc
Tracefile 2:	CONOPT-1.trc
Solvers used :	IPOPT-MUMPS
	CONOPT
Modeltype(s)	`NLP`

	CONOPT: optimal	CONOPT: locally optimal	CONOPT: feasible	CONOPT: infeasible	CONOPT: unbounded	CONOPT: fail	CONOPT: no data	total IPOPT-MUMPS
IPOPT-MUMPS: optimal	-	-	-	-	-	-	-	`-`
IPOPT-MUMPS: locally optimal	-	`68`	-	-	-	`4`	-	`72`
IPOPT-MUMPS: feasible	-	`2`	-	-	-	-	-	`2`
IPOPT-MUMPS: infeasible	-	`1`	`1`	`1`	-	-	-	`3`
IPOPT-MUMPS: unbounded	-	-	-	-	-	-	-	`-`
IPOPT-MUMPS: fail	-	`1`	-	`2`	`1`	-	-	`4`
IPOPT-MUMPS: no data	-	-	-	-	-	-	-	`-`
total CONOPT	`-`	`72`	`1`	`3`	`1`	`4`	`-`	`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-MUMPS: locally optimal -- CONOPT: locally optimal

Modelname	Time (IPOPT-MUMPS)	Time (CONOPT)	Ratio (IPOPT-MUMPS/CONOPT)	Obj (IPOPT-MUMPS)	Obj (CONOPT)
`arki0002`	`0.3320`	`0.9630`	`0.345`	`1.87252774`	`1.08668302`
`arki0004`	`2.7390`	`3.3540`	`0.817`	`323.46703883`	`327.73301341`
`arki0011`	`93.2640`	`6.5860`	`14.161`	`-224086.45997864`	`-224086.46003881`
`arki0013`	`146.4110`	`745.9290`	`0.196`	`-224253.08644157`	`-224253.08922164`
`arki0015`	`4.5130`	`0.7570`	`5.962`	`-266.94068809`	`-271.73572350`
`arki0016`	`16.7380`	`1107.5970`	`0.015`	`867.97316601`	`867.97316601`
`arki0017`	`1.4940`	`94.5180`	`0.016`	`-121.83308011`	`-121.83308010`
`arki0018`	`0.6620`	`1.2720`	`0.520`	`0.01045662`	`0.01045662`
`arki0020`	`0.1470`	`0.2000`	`0.735`	`-41.07495436`	`-41.07495436`
`arki0021`	`0.4450`	`0.9070`	`0.491`	`-72.58210091`	`-72.58210091`
`arki0022`	`0.7380`	`1.1870`	`0.622`	`-87.09909127`	`-87.09909127`
`arki0023`	`1.4360`	`3.7120`	`0.387`	`-153.66007775`	`-153.66007775`
`camshape400`	`1.4250`	`0.0460`	`30.978`	`-4.27569663`	`-4.27568848`
`camshape800`	`559.8860`	`0.2300`	`2434.287`	`-4.27430687`	`-4.27427414`
`catmix100`	`0.0840`	`0.0460`	`1.826`	`-0.04806941`	`-0.04806940`
`catmix200`	`0.0900`	`0.0550`	`1.636`	`-0.04805914`	`-0.04805914`
`catmix400`	`0.1640`	`0.1440`	`1.139`	`-0.04805654`	`-0.04805654`
`catmix800`	`0.2790`	`0.4500`	`0.620`	`-0.04805590`	`-0.04805590`
`chain400`	`0.0610`	`0.1190`	`0.513`	`5.06862169`	`5.06862169`
`elec200`	`19.5520`	`9.6280`	`2.031`	`18439.26774952`	`18438.91507542`
`ex8_2_2a`	`3.7210`	`7.5910`	`0.490`	`-552.66625903`	`-552.66625942`
`ex8_2_2b`	`5.0930`	`9.0010`	`0.566`	`-552.66625998`	`-552.66625902`
`ex8_2_3a`	`7.3830`	`20.6320`	`0.358`	`-3731.07929678`	`-3731.07929501`
`ex8_2_3b`	`8.6350`	`20.5010`	`0.421`	`-3731.07929695`	`-3731.07929518`
`ex8_2_5a`	`2.2240`	`3.2450`	`0.685`	`-830.33806763`	`-830.33806704`
`ex8_2_5b`	`3.8270`	`2.9900`	`1.280`	`-830.33806763`	`-830.33806698`
`flowchan100`	`0.1070`	`0.0420`	`2.548`	`0.00000000`	`0.00000000`
`flowchan200`	`0.2160`	`0.1220`	`1.770`	`0.00000000`	`0.00000000`
`flowchan400`	`0.4320`	`0.2910`	`1.485`	`0.00000000`	`0.00000000`
`gasoil100`	`0.4290`	`0.1860`	`2.306`	`0.00523659`	`0.00523659`
`gasoil200`	`0.7050`	`0.3930`	`1.794`	`0.00523660`	`0.00523660`
`gasoil400`	`1.5490`	`0.8620`	`1.797`	`0.00523660`	`0.00523660`
`gasoil50`	`0.1690`	`0.0970`	`1.742`	`0.00523664`	`0.00523664`
`infeas1`	`0.7390`	`0.2410`	`3.066`	`13685.59647017`	`13685.59646095`
`jbearing100`	`0.7220`	`0.5080`	`1.421`	`-0.15504194`	`-0.15504196`
`jbearing25`	`0.1740`	`1.4170`	`0.123`	`-0.15401551`	`-0.15401554`
`jbearing50`	`0.3200`	`0.1920`	`1.667`	`-0.15482381`	`-0.15482422`
`jbearing75`	`0.5130`	`0.3430`	`1.496`	`-0.15498446`	`-0.15498453`
`lnts100`	`0.0900`	`0.1230`	`0.732`	`0.55459540`	`0.55459540`
`lnts200`	`0.1420`	`0.3110`	`0.457`	`0.55457702`	`0.55457702`
`lnts400`	`0.2830`	`0.9830`	`0.288`	`0.55457241`	`0.55457241`
`methanol100`	`0.4600`	`0.1830`	`2.514`	`0.00902229`	`0.00902229`
`methanol200`	`4.5890`	`0.3870`	`11.858`	`0.00902229`	`0.00902229`
`methanol400`	`5.3420`	`0.9160`	`5.832`	`0.00902229`	`0.00902229`
`methanol50`	`0.1660`	`0.0910`	`1.824`	`0.00902229`	`0.00902229`
`minsurf100`	`0.7840`	`0.5520`	`1.420`	`2.50694962`	`2.50694926`
`minsurf25`	`0.1680`	`0.8990`	`0.187`	`2.51948798`	`2.51948768`
`minsurf50`	`0.3480`	`0.1680`	`2.071`	`2.51489003`	`2.51488916`
`minsurf75`	`2.0900`	`0.3050`	`6.852`	`2.50568665`	`2.50568648`
`pinene100`	`0.4770`	`0.3440`	`1.387`	`19.87217015`	`19.87217014`
`pinene200`	`0.9780`	`1.4160`	`0.691`	`19.87216684`	`19.87216684`
`pinene25`	`0.2660`	`0.2330`	`1.142`	`19.87216552`	`19.87216067`
`pinene50`	`0.2630`	`0.2330`	`1.129`	`19.87216552`	`19.87216067`
`polygon100`	`1.5450`	`5.4050`	`0.286`	`-0.78505614`	`-0.78486056`
`polygon25`	`0.0910`	`0.1040`	`0.875`	`-0.77974054`	`-0.77825010`
`polygon50`	`1.1850`	`0.5740`	`2.064`	`-0.78213256`	`-0.78306429`
`polygon75`	`3.0070`	`2.7700`	`1.086`	`-0.78446376`	`-0.78441600`
`popdynm100`	`0.5200`	`3.3110`	`0.157`	`19746.52860214`	`19746.52860217`
`popdynm200`	`1.2240`	`4.4270`	`0.276`	`19746.52964658`	`19746.52964660`
`popdynm25`	`0.2880`	`1.1360`	`0.254`	`19752.21541508`	`19752.21541511`
`popdynm50`	`1.0060`	`0.8220`	`1.224`	`19746.54515625`	`19746.54515628`
`robot200`	`0.8960`	`0.8580`	`1.044`	`9.14139688`	`9.14139550`
`robot400`	`2.7410`	`1.7430`	`1.573`	`9.14102607`	`9.14102603`
`rocket400`	`920.4500`	`7.3270`	`125.624`	`-1.01283661`	`-1.01283660`
`torsion100`	`0.7580`	`2.8130`	`0.269`	`-0.41823920`	`-0.41823921`
`torsion25`	`0.1630`	`0.5190`	`0.314`	`-0.41751073`	`-0.41751073`
`torsion50`	`0.3800`	`1.1460`	`0.332`	`-0.41808762`	`-0.41808763`
`torsion75`	`0.5740`	`2.1170`	`0.271`	`-0.41819939`	`-0.41819940`

IPOPT-MUMPS: locally optimal -- CONOPT: fail

Modelname	Time (IPOPT-MUMPS)	Time (CONOPT)	Ratio (IPOPT-MUMPS/CONOPT)	Obj (IPOPT-MUMPS)	Status (CONOPT)
`arki0012`	`89.1190`	`15.0240`	---	`-224252.27283280`	`mstat( 6)sstat( 4)`
`arki0014`	`88.4720`	`11.0840`	---	`-223976.64178451`	`mstat( 6)sstat( 4)`
`rocket100`	`9.7010`	`0.6340`	---	`-1.01283202`	`mstat( 6)sstat( 4)`
`rocket200`	`78.3440`	`1.0570`	---	`-1.01283569`	`mstat( 6)sstat( 4)`

IPOPT-MUMPS: feasible -- CONOPT: locally optimal

Modelname	Time (IPOPT-MUMPS)	Time (CONOPT)	Ratio (IPOPT-MUMPS/CONOPT)	Obj (IPOPT-MUMPS)	Obj (CONOPT)
`arki0003`	`3606.7630`	`5.0250`	`717.764`	`0.00000000`	`3795.20606743`
`robot50`	`3610.4260`	`0.1010`	`35746.792`	`0.00000000`	`9.14687850`

IPOPT-MUMPS: infeasible -- CONOPT: locally optimal

Modelname	Time (IPOPT-MUMPS)	Time (CONOPT)	Ratio (IPOPT-MUMPS/CONOPT)	Status (IPOPT-MUMPS)	Obj (CONOPT)
`glider50`	`0.7920`	`6.9400`	---	`mstat( 5)sstat( 1)`	`-1286.97737315`

IPOPT-MUMPS: infeasible -- CONOPT: feasible

Modelname	Time (IPOPT-MUMPS)	Time (CONOPT)	Ratio (IPOPT-MUMPS/CONOPT)	Status (IPOPT-MUMPS)	Obj (CONOPT)
`glider400`	`8.5880`	`45.2300`	---	`mstat( 5)sstat( 1)`	`-298.24695974`

IPOPT-MUMPS: infeasible -- CONOPT: infeasible

Modelname	Time (IPOPT-MUMPS)	Time (CONOPT)	Ratio (IPOPT-MUMPS/CONOPT)	Status (IPOPT-MUMPS)	Status (CONOPT)
`glider100`	`2.0810`	`3.3770`	---	`mstat( 5)sstat( 1)`	`mstat( 5)sstat( 1)`

IPOPT-MUMPS: fail -- CONOPT: locally optimal

Modelname	Time (IPOPT-MUMPS)	Time (CONOPT)	Ratio (IPOPT-MUMPS/CONOPT)	Status (IPOPT-MUMPS)	Obj (CONOPT)
`robot100`	`3606.1300`	`0.2140`	---	`mstat( 6)sstat( 3)`	`9.14268538`

IPOPT-MUMPS: fail -- CONOPT: infeasible

Modelname	Time (IPOPT-MUMPS)	Time (CONOPT)	Ratio (IPOPT-MUMPS/CONOPT)	Status (IPOPT-MUMPS)	Status (CONOPT)
`arki0008`	`NA`	`24.1840`	---	`mstat(13)sstat(13)`	`mstat( 5)sstat( 1)`
`glider200`	`3672.8230`	`6.6630`	---	`mstat( 6)sstat( 3)`	`mstat( 5)sstat( 1)`

IPOPT-MUMPS: fail -- CONOPT: unbounded

Modelname	Time (IPOPT-MUMPS)	Time (CONOPT)	Ratio (IPOPT-MUMPS/CONOPT)	Status (IPOPT-MUMPS)	Status (CONOPT)
`ex8_2_2`	`NA`	`1.7750`	---	`mstat(13)sstat(13)`	`mstat( 3)sstat( 1)`

IPOPT-MUMPS: locally optimal:

Modelname	Time (IPOPT-MUMPS)	Obj (IPOPT-MUMPS)
`arki0002`	`0.3320`	`1.87252774`
`arki0004`	`2.7390`	`323.46703883`
`arki0011`	`93.2640`	`-224086.45997864`
`arki0012`	`89.1190`	`-224252.27283280`
`arki0013`	`146.4110`	`-224253.08644157`
`arki0014`	`88.4720`	`-223976.64178451`
`arki0015`	`4.5130`	`-266.94068809`
`arki0016`	`16.7380`	`867.97316601`
`arki0017`	`1.4940`	`-121.83308011`
`arki0018`	`0.6620`	`0.01045662`
`arki0020`	`0.1470`	`-41.07495436`
`arki0021`	`0.4450`	`-72.58210091`
`arki0022`	`0.7380`	`-87.09909127`
`arki0023`	`1.4360`	`-153.66007775`
`camshape400`	`1.4250`	`-4.27569663`
`camshape800`	`559.8860`	`-4.27430687`
`catmix100`	`0.0840`	`-0.04806941`
`catmix200`	`0.0900`	`-0.04805914`
`catmix400`	`0.1640`	`-0.04805654`
`catmix800`	`0.2790`	`-0.04805590`
`chain400`	`0.0610`	`5.06862169`
`elec200`	`19.5520`	`18439.26774952`
`ex8_2_2a`	`3.7210`	`-552.66625903`
`ex8_2_2b`	`5.0930`	`-552.66625998`
`ex8_2_3a`	`7.3830`	`-3731.07929678`
`ex8_2_3b`	`8.6350`	`-3731.07929695`
`ex8_2_5a`	`2.2240`	`-830.33806763`
`ex8_2_5b`	`3.8270`	`-830.33806763`
`flowchan100`	`0.1070`	`0.00000000`
`flowchan200`	`0.2160`	`0.00000000`
`flowchan400`	`0.4320`	`0.00000000`
`gasoil100`	`0.4290`	`0.00523659`
`gasoil200`	`0.7050`	`0.00523660`
`gasoil400`	`1.5490`	`0.00523660`
`gasoil50`	`0.1690`	`0.00523664`
`infeas1`	`0.7390`	`13685.59647017`
`jbearing100`	`0.7220`	`-0.15504194`
`jbearing25`	`0.1740`	`-0.15401551`
`jbearing50`	`0.3200`	`-0.15482381`
`jbearing75`	`0.5130`	`-0.15498446`
`lnts100`	`0.0900`	`0.55459540`
`lnts200`	`0.1420`	`0.55457702`
`lnts400`	`0.2830`	`0.55457241`
`methanol100`	`0.4600`	`0.00902229`
`methanol200`	`4.5890`	`0.00902229`
`methanol400`	`5.3420`	`0.00902229`
`methanol50`	`0.1660`	`0.00902229`
`minsurf100`	`0.7840`	`2.50694962`
`minsurf25`	`0.1680`	`2.51948798`
`minsurf50`	`0.3480`	`2.51489003`
`minsurf75`	`2.0900`	`2.50568665`
`pinene100`	`0.4770`	`19.87217015`
`pinene200`	`0.9780`	`19.87216684`
`pinene25`	`0.2660`	`19.87216552`
`pinene50`	`0.2630`	`19.87216552`
`polygon100`	`1.5450`	`-0.78505614`
`polygon25`	`0.0910`	`-0.77974054`
`polygon50`	`1.1850`	`-0.78213256`
`polygon75`	`3.0070`	`-0.78446376`
`popdynm100`	`0.5200`	`19746.52860214`
`popdynm200`	`1.2240`	`19746.52964658`
`popdynm25`	`0.2880`	`19752.21541508`
`popdynm50`	`1.0060`	`19746.54515625`
`robot200`	`0.8960`	`9.14139688`
`robot400`	`2.7410`	`9.14102607`
`rocket100`	`9.7010`	`-1.01283202`
`rocket200`	`78.3440`	`-1.01283569`
`rocket400`	`920.4500`	`-1.01283661`
`torsion100`	`0.7580`	`-0.41823920`
`torsion25`	`0.1630`	`-0.41751073`
`torsion50`	`0.3800`	`-0.41808762`
`torsion75`	`0.5740`	`-0.41819939`

IPOPT-MUMPS: feasible:

Modelname	Time (IPOPT-MUMPS)	Obj (IPOPT-MUMPS)
`arki0003`	`3606.7630`	`0.00000000`
`robot50`	`3610.4260`	`0.00000000`

IPOPT-MUMPS: infeasible:

Modelname	Time (IPOPT-MUMPS)	Status (IPOPT-MUMPS)
`glider100`	`--`	`mstat( 5) sstat( 1)`
`glider400`	`--`	`mstat( 5) sstat( 1)`
`glider50`	`--`	`mstat( 5) sstat( 1)`

IPOPT-MUMPS: fail:

Modelname	Time (IPOPT-MUMPS)	Status (IPOPT-MUMPS)
`arki0008`	`--`	`mstat(13) sstat(13)`
`ex8_2_2`	`--`	`mstat(13) sstat(13)`
`glider200`	`--`	`mstat( 6) sstat( 3)`
`robot100`	`--`	`mstat( 6) sstat( 3)`

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)`

IPOPT-MUMPS: all -- CONOPT: all

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

Modelname	Time (IPOPT-MUMPS)	Time (CONOPT)	Ratio (IPOPT-MUMPS/ CONOPT)	Obj (IPOPT-MUMPS)	Obj (CONOPT)
`arki0002`	`0.3320`	`0.9630`	`0.345`	`1.87252774`	`1.08668302`
`arki0003`	`3606.7630`	`5.0250`	`717.764`	`0.00000000`	`3795.20606743`
`arki0004`	`2.7390`	`3.3540`	`0.817`	`323.46703883`	`327.73301341`
`arki0008`	`NA`	`24.1840`	---	`mstat(13) sstat(13)`	`mstat( 5) sstat(1)`
`arki0011`	`93.2640`	`6.5860`	`14.161`	`-224086.45997864`	`-224086.46003881`
`arki0012`	`89.1190`	`15.0240`	---	`-224252.27283280`	`mstat( 6) sstat(4)`
`arki0013`	`146.4110`	`745.9290`	`0.196`	`-224253.08644157`	`-224253.08922164`
`arki0014`	`88.4720`	`11.0840`	---	`-223976.64178451`	`mstat( 6) sstat(4)`
`arki0015`	`4.5130`	`0.7570`	`5.962`	`-266.94068809`	`-271.73572350`
`arki0016`	`16.7380`	`1107.5970`	`0.015`	`867.97316601`	`867.97316601`
`arki0017`	`1.4940`	`94.5180`	`0.016`	`-121.83308011`	`-121.83308010`
`arki0018`	`0.6620`	`1.2720`	`0.520`	`0.01045662`	`0.01045662`
`arki0020`	`0.1470`	`0.2000`	`0.735`	`-41.07495436`	`-41.07495436`
`arki0021`	`0.4450`	`0.9070`	`0.491`	`-72.58210091`	`-72.58210091`
`arki0022`	`0.7380`	`1.1870`	`0.622`	`-87.09909127`	`-87.09909127`
`arki0023`	`1.4360`	`3.7120`	`0.387`	`-153.66007775`	`-153.66007775`
`camshape400`	`1.4250`	`0.0460`	`30.978`	`-4.27569663`	`-4.27568848`
`camshape800`	`559.8860`	`0.2300`	`2434.287`	`-4.27430687`	`-4.27427414`
`catmix100`	`0.0840`	`0.0460`	`1.826`	`-0.04806941`	`-0.04806940`
`catmix200`	`0.0900`	`0.0550`	`1.636`	`-0.04805914`	`-0.04805914`
`catmix400`	`0.1640`	`0.1440`	`1.139`	`-0.04805654`	`-0.04805654`
`catmix800`	`0.2790`	`0.4500`	`0.620`	`-0.04805590`	`-0.04805590`
`chain400`	`0.0610`	`0.1190`	`0.513`	`5.06862169`	`5.06862169`
`elec200`	`19.5520`	`9.6280`	`2.031`	`18439.26774952`	`18438.91507542`
`ex8_2_2`	`NA`	`1.7750`	---	`mstat(13) sstat(13)`	`mstat( 3) sstat(1)`
`ex8_2_2a`	`3.7210`	`7.5910`	`0.490`	`-552.66625903`	`-552.66625942`
`ex8_2_2b`	`5.0930`	`9.0010`	`0.566`	`-552.66625998`	`-552.66625902`
`ex8_2_3a`	`7.3830`	`20.6320`	`0.358`	`-3731.07929678`	`-3731.07929501`
`ex8_2_3b`	`8.6350`	`20.5010`	`0.421`	`-3731.07929695`	`-3731.07929518`
`ex8_2_5a`	`2.2240`	`3.2450`	`0.685`	`-830.33806763`	`-830.33806704`
`ex8_2_5b`	`3.8270`	`2.9900`	`1.280`	`-830.33806763`	`-830.33806698`
`flowchan100`	`0.1070`	`0.0420`	`2.548`	`0.00000000`	`0.00000000`
`flowchan200`	`0.2160`	`0.1220`	`1.770`	`0.00000000`	`0.00000000`
`flowchan400`	`0.4320`	`0.2910`	`1.485`	`0.00000000`	`0.00000000`
`gasoil100`	`0.4290`	`0.1860`	`2.306`	`0.00523659`	`0.00523659`
`gasoil200`	`0.7050`	`0.3930`	`1.794`	`0.00523660`	`0.00523660`
`gasoil400`	`1.5490`	`0.8620`	`1.797`	`0.00523660`	`0.00523660`
`gasoil50`	`0.1690`	`0.0970`	`1.742`	`0.00523664`	`0.00523664`
`glider100`	`2.0810`	`3.3770`	---	`mstat( 5) sstat(1)`	`mstat( 5) sstat(1)`
`glider200`	`3672.8230`	`6.6630`	---	`mstat( 6) sstat(3)`	`mstat( 5) sstat(1)`
`glider400`	`8.5880`	`45.2300`	---	`mstat( 5) sstat(1)`	`-298.24695974`
`glider50`	`0.7920`	`6.9400`	---	`mstat( 5) sstat(1)`	`-1286.97737315`
`infeas1 (max)`	`0.7390`	`0.2410`	`3.066`	`13685.59647017`	`13685.59646095`
`jbearing100`	`0.7220`	`0.5080`	`1.421`	`-0.15504194`	`-0.15504196`
`jbearing25`	`0.1740`	`1.4170`	`0.123`	`-0.15401551`	`-0.15401554`
`jbearing50`	`0.3200`	`0.1920`	`1.667`	`-0.15482381`	`-0.15482422`
`jbearing75`	`0.5130`	`0.3430`	`1.496`	`-0.15498446`	`-0.15498453`
`lnts100`	`0.0900`	`0.1230`	`0.732`	`0.55459540`	`0.55459540`
`lnts200`	`0.1420`	`0.3110`	`0.457`	`0.55457702`	`0.55457702`
`lnts400`	`0.2830`	`0.9830`	`0.288`	`0.55457241`	`0.55457241`
`methanol100`	`0.4600`	`0.1830`	`2.514`	`0.00902229`	`0.00902229`
`methanol200`	`4.5890`	`0.3870`	`11.858`	`0.00902229`	`0.00902229`
`methanol400`	`5.3420`	`0.9160`	`5.832`	`0.00902229`	`0.00902229`
`methanol50`	`0.1660`	`0.0910`	`1.824`	`0.00902229`	`0.00902229`
`minsurf100`	`0.7840`	`0.5520`	`1.420`	`2.50694962`	`2.50694926`
`minsurf25`	`0.1680`	`0.8990`	`0.187`	`2.51948798`	`2.51948768`
`minsurf50`	`0.3480`	`0.1680`	`2.071`	`2.51489003`	`2.51488916`
`minsurf75`	`2.0900`	`0.3050`	`6.852`	`2.50568665`	`2.50568648`
`pinene100`	`0.4770`	`0.3440`	`1.387`	`19.87217015`	`19.87217014`
`pinene200`	`0.9780`	`1.4160`	`0.691`	`19.87216684`	`19.87216684`
`pinene25`	`0.2660`	`0.2330`	`1.142`	`19.87216552`	`19.87216067`
`pinene50`	`0.2630`	`0.2330`	`1.129`	`19.87216552`	`19.87216067`
`polygon100`	`1.5450`	`5.4050`	`0.286`	`-0.78505614`	`-0.78486056`
`polygon25`	`0.0910`	`0.1040`	`0.875`	`-0.77974054`	`-0.77825010`
`polygon50`	`1.1850`	`0.5740`	`2.064`	`-0.78213256`	`-0.78306429`
`polygon75`	`3.0070`	`2.7700`	`1.086`	`-0.78446376`	`-0.78441600`
`popdynm100`	`0.5200`	`3.3110`	`0.157`	`19746.52860214`	`19746.52860217`
`popdynm200`	`1.2240`	`4.4270`	`0.276`	`19746.52964658`	`19746.52964660`
`popdynm25`	`0.2880`	`1.1360`	`0.254`	`19752.21541508`	`19752.21541511`
`popdynm50`	`1.0060`	`0.8220`	`1.224`	`19746.54515625`	`19746.54515628`
`robot100`	`3606.1300`	`0.2140`	---	`mstat( 6) sstat(3)`	`9.14268538`
`robot200`	`0.8960`	`0.8580`	`1.044`	`9.14139688`	`9.14139550`
`robot400`	`2.7410`	`1.7430`	`1.573`	`9.14102607`	`9.14102603`
`robot50`	`3610.4260`	`0.1010`	`35746.792`	`0.00000000`	`9.14687850`
`rocket100`	`9.7010`	`0.6340`	---	`-1.01283202`	`mstat( 6) sstat(4)`
`rocket200`	`78.3440`	`1.0570`	---	`-1.01283569`	`mstat( 6) sstat(4)`
`rocket400`	`920.4500`	`7.3270`	`125.624`	`-1.01283661`	`-1.01283660`
`torsion100`	`0.7580`	`2.8130`	`0.269`	`-0.41823920`	`-0.41823921`
`torsion25`	`0.1630`	`0.5190`	`0.314`	`-0.41751073`	`-0.41751073`
`torsion50`	`0.3800`	`1.1460`	`0.332`	`-0.41808762`	`-0.41808763`
`torsion75`	`0.5740`	`2.1170`	`0.271`	`-0.41819939`	`-0.41819940`