Solver Square Comparison

Solver Square Comparison: Considers all models.

Results created on 11/09/09 18:57:37 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 COINIPOPTDma27 is represented on the left (rows) and solver IPOPTmumps 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:	COINIPOPTD-1.trc
Tracefile 2:	IPOPT-2.trc
Solvers used :	COINIPOPTDma27
	IPOPTmumps
Modeltype(s)	`NLP`

	IPOPTmumps: optimal	IPOPTmumps: locally optimal	IPOPTmumps: feasible	IPOPTmumps: infeasible	IPOPTmumps: unbounded	IPOPTmumps: fail	IPOPTmumps: no data	total COINIPOPTDma27
COINIPOPTDma27: optimal	-	`13`	-	-	-	-	-	`13`
COINIPOPTDma27: locally optimal	-	`59`	-	-	-	`1`	-	`60`
COINIPOPTDma27: feasible	-	-	-	-	-	-	-	`-`
COINIPOPTDma27: infeasible	-	-	-	`3`	-	-	-	`3`
COINIPOPTDma27: unbounded	-	-	-	-	-	`1`	-	`1`
COINIPOPTDma27: fail	-	-	-	`1`	`1`	`2`	-	`4`
COINIPOPTDma27: no data	-	-	-	-	-	-	-	`-`
total IPOPTmumps	`-`	`72`	`-`	`4`	`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.

COINIPOPTDma27: optimal -- IPOPTmumps: locally optimal

Modelname	Time (COINIPOPTDma27)	Time (IPOPTmumps)	Ratio (COINIPOPTDma27/IPOPTmumps)	Obj (COINIPOPTDma27)	Obj (IPOPTmumps)
`arki0018`	`0.2970`	`0.8300`	`0.358`	`0.01045662`	`0.01045662`
`arki0020`	`0.0580`	`0.2600`	`0.223`	`-41.07495436`	`-41.07495436`
`arki0021`	`0.1720`	`1.3700`	`0.126`	`-72.58210091`	`-72.58210091`
`arki0022`	`0.2960`	`2.4900`	`0.119`	`-87.09909127`	`-87.09909127`
`arki0023`	`0.5750`	`9.0600`	`0.063`	`-153.66007775`	`-153.66007775`
`jbearing100`	`0.4000`	`7.2100`	`0.055`	`-0.15504194`	`-0.15504194`
`jbearing25`	`0.1070`	`0.5800`	`0.184`	`-0.15401551`	`-0.15401551`
`jbearing50`	`0.2010`	`1.7700`	`0.114`	`-0.15482381`	`-0.15482381`
`jbearing75`	`0.2780`	`3.9800`	`0.070`	`-0.15498446`	`-0.15498446`
`minsurf100`	`0.5260`	`9.1700`	`0.057`	`2.50694962`	`2.50694962`
`minsurf25`	`0.1450`	`0.6500`	`0.223`	`2.51948798`	`2.51948798`
`minsurf50`	`0.2360`	`2.2900`	`0.103`	`2.51489003`	`2.51489003`
`minsurf75`	`1.3620`	`14.7400`	`0.092`	`2.50568661`	`2.50568709`

COINIPOPTDma27: locally optimal -- IPOPTmumps: locally optimal

Modelname	Time (COINIPOPTDma27)	Time (IPOPTmumps)	Ratio (COINIPOPTDma27/IPOPTmumps)	Obj (COINIPOPTDma27)	Obj (IPOPTmumps)
`arki0002`	`0.5130`	`0.2800`	`1.832`	`1.87252774`	`1.87252774`
`arki0004`	`2.4100`	`4.9200`	`0.490`	`323.46703883`	`327.73301341`
`arki0011`	`73.2350`	`115.0700`	`0.636`	`-224086.46003464`	`-224086.45996109`
`arki0012`	`56.1550`	`152.7100`	`0.368`	`-224252.42629882`	`-224252.44284664`
`arki0013`	`60.8560`	`119.2700`	`0.510`	`-224253.08745620`	`-224253.08150466`
`arki0014`	`50.4280`	`122.7900`	`0.411`	`-223977.03530617`	`-223977.07395310`
`arki0015`	`2.6520`	`5.4700`	`0.485`	`-266.94068809`	`-266.94068809`
`arki0016`	`11.9170`	`15.7500`	`0.757`	`867.97316601`	`867.97316601`
`arki0017`	`0.4020`	`1.4300`	`0.281`	`-121.83308011`	`-121.83308011`
`camshape400`	`0.1590`	`1.3200`	`0.120`	`-4.27569663`	`-4.27569663`
`camshape800`	`0.3430`	`167.6800`	`0.002`	`-4.27430687`	`-4.27430687`
`catmix100`	`0.0390`	`0.0600`	`0.650`	`-0.04806941`	`-0.04806941`
`catmix200`	`0.0450`	`0.0900`	`0.500`	`-0.04805914`	`-0.04805914`
`catmix400`	`0.0840`	`0.1400`	`0.600`	`-0.04805654`	`-0.04805654`
`catmix800`	`0.1620`	`0.2800`	`0.579`	`-0.04805590`	`-0.04805590`
`chain400`	`0.0160`	`0.0700`	`0.229`	`5.06862169`	`5.06862169`
`elec200`	`58.4470`	`1213.6100`	`0.048`	`18439.26774952`	`18439.26774952`
`ex8_2_2a`	`2.5940`	`4.4700`	`0.580`	`-552.66625903`	`-552.66625903`
`ex8_2_2b`	`3.0450`	`6.0400`	`0.504`	`-552.66625998`	`-552.66625998`
`ex8_2_3a`	`7.1170`	`10.6100`	`0.671`	`-3731.07929678`	`-3731.07929678`
`ex8_2_3b`	`8.1910`	`12.4600`	`0.657`	`-3731.07929695`	`-3731.07929695`
`ex8_2_5a`	`2.3930`	`3.4800`	`0.688`	`-830.33806763`	`-830.33806763`
`ex8_2_5b`	`8.7250`	`10.7900`	`0.809`	`-830.33806763`	`-830.33806763`
`flowchan100`	`0.0450`	`0.1000`	`0.450`	`0.00000000`	`0.00000000`
`flowchan200`	`0.0910`	`0.1900`	`0.479`	`0.00000000`	`0.00000000`
`flowchan400`	`0.4490`	`0.4100`	`1.095`	`0.00000000`	`0.00000000`
`gasoil100`	`0.2030`	`0.3800`	`0.534`	`0.00523659`	`0.00523659`
`gasoil200`	`0.3470`	`0.6800`	`0.510`	`0.00523660`	`0.00523660`
`gasoil400`	`0.9890`	`1.6100`	`0.614`	`0.00523660`	`0.00523660`
`gasoil50`	`0.1190`	`0.1500`	`0.793`	`0.00523664`	`0.00523664`
`infeas1`	`0.3760`	`0.7000`	`0.537`	`13685.59647017`	`13685.59647018`
`lnts100`	`0.0280`	`0.1100`	`0.255`	`0.55459540`	`0.55459540`
`lnts200`	`0.0430`	`0.1300`	`0.331`	`0.55457702`	`0.55457702`
`lnts400`	`0.0830`	`0.2600`	`0.319`	`0.55457241`	`0.55457241`
`methanol100`	`0.2520`	`0.5000`	`0.504`	`0.00902229`	`0.00902229`
`methanol200`	`2.2430`	`7.5500`	`0.297`	`0.00902229`	`0.00902229`
`methanol400`	`4.5550`	`6.9700`	`0.654`	`0.00902229`	`0.00902229`
`methanol50`	`0.0810`	`0.1600`	`0.506`	`0.00902229`	`0.00902229`
`pinene100`	`0.1680`	`0.4400`	`0.382`	`19.87217015`	`19.87217015`
`pinene200`	`0.4250`	`0.9100`	`0.467`	`19.87216684`	`19.87216684`
`pinene25`	`0.0810`	`0.2400`	`0.338`	`19.87216552`	`19.87216552`
`pinene50`	`0.0810`	`0.2600`	`0.312`	`19.87216552`	`19.87216552`
`polygon100`	`3.7980`	`5.0700`	`0.749`	`-0.78505614`	`-0.78505614`
`polygon25`	`0.0350`	`0.1000`	`0.350`	`-0.77974054`	`-0.77974054`
`polygon50`	`0.6580`	`1.5500`	`0.425`	`-0.78213256`	`-0.78213256`
`polygon75`	`2.8940`	`6.2900`	`0.460`	`-0.78446376`	`-0.78446376`
`popdynm100`	`0.2590`	`0.5100`	`0.508`	`19746.52860214`	`19746.52860214`
`popdynm200`	`0.6550`	`1.4100`	`0.465`	`19746.52964658`	`19746.52964658`
`popdynm25`	`0.0990`	`0.3200`	`0.309`	`19752.21541508`	`19752.21541508`
`popdynm50`	`0.1490`	`0.7200`	`0.207`	`19746.54515625`	`19746.54515625`
`robot200`	`0.2740`	`0.8600`	`0.319`	`9.14139686`	`9.14139688`
`robot400`	`0.7520`	`2.6500`	`0.284`	`9.14102607`	`9.14102607`
`rocket100`	`1.8710`	`5.7200`	`0.327`	`-1.01283202`	`-1.01283202`
`rocket200`	`12.0200`	`33.5700`	`0.358`	`-1.01283569`	`-1.01283569`
`rocket400`	`118.6340`	`255.5200`	`0.464`	`-1.01283661`	`-1.01283661`
`torsion100`	`0.5540`	`13.6900`	`0.040`	`-0.41823920`	`-0.41823920`
`torsion25`	`0.1320`	`0.8600`	`0.153`	`-0.41751073`	`-0.41751073`
`torsion50`	`0.2660`	`3.6800`	`0.072`	`-0.41808762`	`-0.41808762`
`torsion75`	`0.4090`	`7.9600`	`0.051`	`-0.41819939`	`-0.41819939`

COINIPOPTDma27: locally optimal -- IPOPTmumps: fail

Modelname	Time (COINIPOPTDma27)	Time (IPOPTmumps)	Ratio (COINIPOPTDma27/IPOPTmumps)	Obj (COINIPOPTDma27)	Status (IPOPTmumps)
`arki0003`	`1499.9250`	`3600.1000`	---	`3795.19682438`	`mstat( 6)sstat( 3)`

COINIPOPTDma27: infeasible -- IPOPTmumps: infeasible

Modelname	Time (COINIPOPTDma27)	Time (IPOPTmumps)	Ratio (COINIPOPTDma27/IPOPTmumps)	Status (COINIPOPTDma27)	Status (IPOPTmumps)
`glider100`	`1.4750`	`2.0800`	---	`mstat( 5)sstat( 1)`	`mstat( 5)sstat( 1)`
`glider400`	`161.1040`	`9.5100`	---	`mstat( 5)sstat( 1)`	`mstat( 5)sstat( 1)`
`glider50`	`0.2920`	`0.7800`	---	`mstat( 5)sstat( 1)`	`mstat( 5)sstat( 1)`

COINIPOPTDma27: unbounded -- IPOPTmumps: fail

Modelname	Time (COINIPOPTDma27)	Time (IPOPTmumps)	Ratio (COINIPOPTDma27/IPOPTmumps)	Status (COINIPOPTDma27)	Status (IPOPTmumps)
`robot100`	`6.4560`	`3600.1300`	---	`mstat( 3)sstat( 1)`	`mstat( 6)sstat( 3)`

COINIPOPTDma27: fail -- IPOPTmumps: infeasible

Modelname	Time (COINIPOPTDma27)	Time (IPOPTmumps)	Ratio (COINIPOPTDma27/IPOPTmumps)	Status (COINIPOPTDma27)	Status (IPOPTmumps)
`glider200`	`3619.9990`	`866.6800`	---	`mstat( 6)sstat( 3)`	`mstat( 5)sstat( 1)`

COINIPOPTDma27: fail -- IPOPTmumps: unbounded

Modelname	Time (COINIPOPTDma27)	Time (IPOPTmumps)	Ratio (COINIPOPTDma27/IPOPTmumps)	Status (COINIPOPTDma27)	Status (IPOPTmumps)
`robot50`	`102.4360`	`43.2100`	---	`mstat( 6)sstat( 4)`	`mstat( 3)sstat( 1)`

COINIPOPTDma27: fail -- IPOPTmumps: fail

Modelname	Time (COINIPOPTDma27)	Time (IPOPTmumps)	Ratio (COINIPOPTDma27/IPOPTmumps)	Status (COINIPOPTDma27)	Status (IPOPTmumps)
`arki0008`	`3627.7850`	`788.1100`	---	`mstat( 6)sstat( 3)`	`mstat( 6)sstat( 4)`
`ex8_2_2`	`3634.5650`	`3637.2900`	---	`mstat( 6)sstat( 3)`	`mstat( 6)sstat( 3)`

COINIPOPTDma27: optimal:

Modelname	Time (COINIPOPTDma27)	Obj (COINIPOPTDma27)
`arki0018`	`0.2970`	`0.01045662`
`arki0020`	`0.0580`	`-41.07495436`
`arki0021`	`0.1720`	`-72.58210091`
`arki0022`	`0.2960`	`-87.09909127`
`arki0023`	`0.5750`	`-153.66007775`
`jbearing100`	`0.4000`	`-0.15504194`
`jbearing25`	`0.1070`	`-0.15401551`
`jbearing50`	`0.2010`	`-0.15482381`
`jbearing75`	`0.2780`	`-0.15498446`
`minsurf100`	`0.5260`	`2.50694962`
`minsurf25`	`0.1450`	`2.51948798`
`minsurf50`	`0.2360`	`2.51489003`
`minsurf75`	`1.3620`	`2.50568661`

COINIPOPTDma27: locally optimal:

Modelname	Time (COINIPOPTDma27)	Obj (COINIPOPTDma27)
`arki0002`	`0.5130`	`1.87252774`
`arki0003`	`1499.9250`	`3795.19682438`
`arki0004`	`2.4100`	`323.46703883`
`arki0011`	`73.2350`	`-224086.46003464`
`arki0012`	`56.1550`	`-224252.42629882`
`arki0013`	`60.8560`	`-224253.08745620`
`arki0014`	`50.4280`	`-223977.03530617`
`arki0015`	`2.6520`	`-266.94068809`
`arki0016`	`11.9170`	`867.97316601`
`arki0017`	`0.4020`	`-121.83308011`
`camshape400`	`0.1590`	`-4.27569663`
`camshape800`	`0.3430`	`-4.27430687`
`catmix100`	`0.0390`	`-0.04806941`
`catmix200`	`0.0450`	`-0.04805914`
`catmix400`	`0.0840`	`-0.04805654`
`catmix800`	`0.1620`	`-0.04805590`
`chain400`	`0.0160`	`5.06862169`
`elec200`	`58.4470`	`18439.26774952`
`ex8_2_2a`	`2.5940`	`-552.66625903`
`ex8_2_2b`	`3.0450`	`-552.66625998`
`ex8_2_3a`	`7.1170`	`-3731.07929678`
`ex8_2_3b`	`8.1910`	`-3731.07929695`
`ex8_2_5a`	`2.3930`	`-830.33806763`
`ex8_2_5b`	`8.7250`	`-830.33806763`
`flowchan100`	`0.0450`	`0.00000000`
`flowchan200`	`0.0910`	`0.00000000`
`flowchan400`	`0.4490`	`0.00000000`
`gasoil100`	`0.2030`	`0.00523659`
`gasoil200`	`0.3470`	`0.00523660`
`gasoil400`	`0.9890`	`0.00523660`
`gasoil50`	`0.1190`	`0.00523664`
`infeas1`	`0.3760`	`13685.59647017`
`lnts100`	`0.0280`	`0.55459540`
`lnts200`	`0.0430`	`0.55457702`
`lnts400`	`0.0830`	`0.55457241`
`methanol100`	`0.2520`	`0.00902229`
`methanol200`	`2.2430`	`0.00902229`
`methanol400`	`4.5550`	`0.00902229`
`methanol50`	`0.0810`	`0.00902229`
`pinene100`	`0.1680`	`19.87217015`
`pinene200`	`0.4250`	`19.87216684`
`pinene25`	`0.0810`	`19.87216552`
`pinene50`	`0.0810`	`19.87216552`
`polygon100`	`3.7980`	`-0.78505614`
`polygon25`	`0.0350`	`-0.77974054`
`polygon50`	`0.6580`	`-0.78213256`
`polygon75`	`2.8940`	`-0.78446376`
`popdynm100`	`0.2590`	`19746.52860214`
`popdynm200`	`0.6550`	`19746.52964658`
`popdynm25`	`0.0990`	`19752.21541508`
`popdynm50`	`0.1490`	`19746.54515625`
`robot200`	`0.2740`	`9.14139686`
`robot400`	`0.7520`	`9.14102607`
`rocket100`	`1.8710`	`-1.01283202`
`rocket200`	`12.0200`	`-1.01283569`
`rocket400`	`118.6340`	`-1.01283661`
`torsion100`	`0.5540`	`-0.41823920`
`torsion25`	`0.1320`	`-0.41751073`
`torsion50`	`0.2660`	`-0.41808762`
`torsion75`	`0.4090`	`-0.41819939`

COINIPOPTDma27: infeasible:

Modelname	Time (COINIPOPTDma27)	Status (COINIPOPTDma27)
`glider100`	`--`	`mstat( 5) sstat( 1)`
`glider400`	`--`	`mstat( 5) sstat( 1)`
`glider50`	`--`	`mstat( 5) sstat( 1)`

COINIPOPTDma27: unbounded:

Modelname	Time (COINIPOPTDma27)	Status (COINIPOPTDma27)
`robot100`	`6.4560`	`mstat( 3) sstat( 1)`

COINIPOPTDma27: fail:

Modelname	Time (COINIPOPTDma27)	Status (COINIPOPTDma27)
`arki0008`	`--`	`mstat( 6) sstat( 3)`
`ex8_2_2`	`--`	`mstat( 6) sstat( 3)`
`glider200`	`--`	`mstat( 6) sstat( 3)`
`robot50`	`--`	`mstat( 6) sstat( 4)`

IPOPTmumps: locally optimal:

Modelname	Time (IPOPTmumps)	Obj (IPOPTmumps)
`arki0002`	`0.2800`	`1.87252774`
`arki0004`	`4.9200`	`327.73301341`
`arki0011`	`115.0700`	`-224086.45996109`
`arki0012`	`152.7100`	`-224252.44284664`
`arki0013`	`119.2700`	`-224253.08150466`
`arki0014`	`122.7900`	`-223977.07395310`
`arki0015`	`5.4700`	`-266.94068809`
`arki0016`	`15.7500`	`867.97316601`
`arki0017`	`1.4300`	`-121.83308011`
`arki0018`	`0.8300`	`0.01045662`
`arki0020`	`0.2600`	`-41.07495436`
`arki0021`	`1.3700`	`-72.58210091`
`arki0022`	`2.4900`	`-87.09909127`
`arki0023`	`9.0600`	`-153.66007775`
`camshape400`	`1.3200`	`-4.27569663`
`camshape800`	`167.6800`	`-4.27430687`
`catmix100`	`0.0600`	`-0.04806941`
`catmix200`	`0.0900`	`-0.04805914`
`catmix400`	`0.1400`	`-0.04805654`
`catmix800`	`0.2800`	`-0.04805590`
`chain400`	`0.0700`	`5.06862169`
`elec200`	`1213.6100`	`18439.26774952`
`ex8_2_2a`	`4.4700`	`-552.66625903`
`ex8_2_2b`	`6.0400`	`-552.66625998`
`ex8_2_3a`	`10.6100`	`-3731.07929678`
`ex8_2_3b`	`12.4600`	`-3731.07929695`
`ex8_2_5a`	`3.4800`	`-830.33806763`
`ex8_2_5b`	`10.7900`	`-830.33806763`
`flowchan100`	`0.1000`	`0.00000000`
`flowchan200`	`0.1900`	`0.00000000`
`flowchan400`	`0.4100`	`0.00000000`
`gasoil100`	`0.3800`	`0.00523659`
`gasoil200`	`0.6800`	`0.00523660`
`gasoil400`	`1.6100`	`0.00523660`
`gasoil50`	`0.1500`	`0.00523664`
`infeas1`	`0.7000`	`13685.59647018`
`jbearing100`	`7.2100`	`-0.15504194`
`jbearing25`	`0.5800`	`-0.15401551`
`jbearing50`	`1.7700`	`-0.15482381`
`jbearing75`	`3.9800`	`-0.15498446`
`lnts100`	`0.1100`	`0.55459540`
`lnts200`	`0.1300`	`0.55457702`
`lnts400`	`0.2600`	`0.55457241`
`methanol100`	`0.5000`	`0.00902229`
`methanol200`	`7.5500`	`0.00902229`
`methanol400`	`6.9700`	`0.00902229`
`methanol50`	`0.1600`	`0.00902229`
`minsurf100`	`9.1700`	`2.50694962`
`minsurf25`	`0.6500`	`2.51948798`
`minsurf50`	`2.2900`	`2.51489003`
`minsurf75`	`14.7400`	`2.50568709`
`pinene100`	`0.4400`	`19.87217015`
`pinene200`	`0.9100`	`19.87216684`
`pinene25`	`0.2400`	`19.87216552`
`pinene50`	`0.2600`	`19.87216552`
`polygon100`	`5.0700`	`-0.78505614`
`polygon25`	`0.1000`	`-0.77974054`
`polygon50`	`1.5500`	`-0.78213256`
`polygon75`	`6.2900`	`-0.78446376`
`popdynm100`	`0.5100`	`19746.52860214`
`popdynm200`	`1.4100`	`19746.52964658`
`popdynm25`	`0.3200`	`19752.21541508`
`popdynm50`	`0.7200`	`19746.54515625`
`robot200`	`0.8600`	`9.14139688`
`robot400`	`2.6500`	`9.14102607`
`rocket100`	`5.7200`	`-1.01283202`
`rocket200`	`33.5700`	`-1.01283569`
`rocket400`	`255.5200`	`-1.01283661`
`torsion100`	`13.6900`	`-0.41823920`
`torsion25`	`0.8600`	`-0.41751073`
`torsion50`	`3.6800`	`-0.41808762`
`torsion75`	`7.9600`	`-0.41819939`

IPOPTmumps: infeasible:

Modelname	Time (IPOPTmumps)	Status (IPOPTmumps)
`glider100`	`--`	`mstat( 5)sstat( 1)`
`glider200`	`--`	`mstat( 5)sstat( 1)`
`glider400`	`--`	`mstat( 5)sstat( 1)`
`glider50`	`--`	`mstat( 5)sstat( 1)`

IPOPTmumps: unbounded:

Modelname	Time (IPOPTmumps)	Status (IPOPTmumps)
`robot50`	`43.2100`	`mstat( 3)sstat( 1)`

IPOPTmumps: fail:

Modelname	Time (IPOPTmumps)	Status (IPOPTmumps)
`arki0003`	`--`	`mstat( 6)sstat( 3)`
`arki0008`	`--`	`mstat( 6)sstat( 4)`
`ex8_2_2`	`--`	`mstat( 6)sstat( 3)`
`robot100`	`--`	`mstat( 6)sstat( 3)`

COINIPOPTDma27: all -- IPOPTmumps: all

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

Modelname	Time (COINIPOPTDma27)	Time (IPOPTmumps)	Ratio (COINIPOPTDma27/ IPOPTmumps)	Obj (COINIPOPTDma27)	Obj (IPOPTmumps)
`arki0002`	`0.5130`	`0.2800`	`1.832`	`1.87252774`	`1.87252774`
`arki0003`	`1499.9250`	`3600.1000`	---	`3795.19682438`	`mstat( 6) sstat(3)`
`arki0004`	`2.4100`	`4.9200`	`0.490`	`323.46703883`	`327.73301341`
`arki0008`	`3627.7850`	`788.1100`	---	`mstat( 6) sstat(3)`	`mstat( 6) sstat(4)`
`arki0011`	`73.2350`	`115.0700`	`0.636`	`-224086.46003464`	`-224086.45996109`
`arki0012`	`56.1550`	`152.7100`	`0.368`	`-224252.42629882`	`-224252.44284664`
`arki0013`	`60.8560`	`119.2700`	`0.510`	`-224253.08745620`	`-224253.08150466`
`arki0014`	`50.4280`	`122.7900`	`0.411`	`-223977.03530617`	`-223977.07395310`
`arki0015`	`2.6520`	`5.4700`	`0.485`	`-266.94068809`	`-266.94068809`
`arki0016`	`11.9170`	`15.7500`	`0.757`	`867.97316601`	`867.97316601`
`arki0017`	`0.4020`	`1.4300`	`0.281`	`-121.83308011`	`-121.83308011`
`arki0018`	`0.2970`	`0.8300`	`0.358`	`0.01045662`	`0.01045662`
`arki0020`	`0.0580`	`0.2600`	`0.223`	`-41.07495436`	`-41.07495436`
`arki0021`	`0.1720`	`1.3700`	`0.126`	`-72.58210091`	`-72.58210091`
`arki0022`	`0.2960`	`2.4900`	`0.119`	`-87.09909127`	`-87.09909127`
`arki0023`	`0.5750`	`9.0600`	`0.063`	`-153.66007775`	`-153.66007775`
`camshape400`	`0.1590`	`1.3200`	`0.120`	`-4.27569663`	`-4.27569663`
`camshape800`	`0.3430`	`167.6800`	`0.002`	`-4.27430687`	`-4.27430687`
`catmix100`	`0.0390`	`0.0600`	`0.650`	`-0.04806941`	`-0.04806941`
`catmix200`	`0.0450`	`0.0900`	`0.500`	`-0.04805914`	`-0.04805914`
`catmix400`	`0.0840`	`0.1400`	`0.600`	`-0.04805654`	`-0.04805654`
`catmix800`	`0.1620`	`0.2800`	`0.579`	`-0.04805590`	`-0.04805590`
`chain400`	`0.0160`	`0.0700`	`0.229`	`5.06862169`	`5.06862169`
`elec200`	`58.4470`	`1213.6100`	`0.048`	`18439.26774952`	`18439.26774952`
`ex8_2_2`	`3634.5650`	`3637.2900`	---	`mstat( 6) sstat(3)`	`mstat( 6) sstat(3)`
`ex8_2_2a`	`2.5940`	`4.4700`	`0.580`	`-552.66625903`	`-552.66625903`
`ex8_2_2b`	`3.0450`	`6.0400`	`0.504`	`-552.66625998`	`-552.66625998`
`ex8_2_3a`	`7.1170`	`10.6100`	`0.671`	`-3731.07929678`	`-3731.07929678`
`ex8_2_3b`	`8.1910`	`12.4600`	`0.657`	`-3731.07929695`	`-3731.07929695`
`ex8_2_5a`	`2.3930`	`3.4800`	`0.688`	`-830.33806763`	`-830.33806763`
`ex8_2_5b`	`8.7250`	`10.7900`	`0.809`	`-830.33806763`	`-830.33806763`
`flowchan100`	`0.0450`	`0.1000`	`0.450`	`0.00000000`	`0.00000000`
`flowchan200`	`0.0910`	`0.1900`	`0.479`	`0.00000000`	`0.00000000`
`flowchan400`	`0.4490`	`0.4100`	`1.095`	`0.00000000`	`0.00000000`
`gasoil100`	`0.2030`	`0.3800`	`0.534`	`0.00523659`	`0.00523659`
`gasoil200`	`0.3470`	`0.6800`	`0.510`	`0.00523660`	`0.00523660`
`gasoil400`	`0.9890`	`1.6100`	`0.614`	`0.00523660`	`0.00523660`
`gasoil50`	`0.1190`	`0.1500`	`0.793`	`0.00523664`	`0.00523664`
`glider100`	`1.4750`	`2.0800`	---	`mstat( 5) sstat(1)`	`mstat( 5) sstat(1)`
`glider200`	`3619.9990`	`866.6800`	---	`mstat( 6) sstat(3)`	`mstat( 5) sstat(1)`
`glider400`	`161.1040`	`9.5100`	---	`mstat( 5) sstat(1)`	`mstat( 5) sstat(1)`
`glider50`	`0.2920`	`0.7800`	---	`mstat( 5) sstat(1)`	`mstat( 5) sstat(1)`
`infeas1 (max)`	`0.3760`	`0.7000`	`0.537`	`13685.59647017`	`13685.59647018`
`jbearing100`	`0.4000`	`7.2100`	`0.055`	`-0.15504194`	`-0.15504194`
`jbearing25`	`0.1070`	`0.5800`	`0.184`	`-0.15401551`	`-0.15401551`
`jbearing50`	`0.2010`	`1.7700`	`0.114`	`-0.15482381`	`-0.15482381`
`jbearing75`	`0.2780`	`3.9800`	`0.070`	`-0.15498446`	`-0.15498446`
`lnts100`	`0.0280`	`0.1100`	`0.255`	`0.55459540`	`0.55459540`
`lnts200`	`0.0430`	`0.1300`	`0.331`	`0.55457702`	`0.55457702`
`lnts400`	`0.0830`	`0.2600`	`0.319`	`0.55457241`	`0.55457241`
`methanol100`	`0.2520`	`0.5000`	`0.504`	`0.00902229`	`0.00902229`
`methanol200`	`2.2430`	`7.5500`	`0.297`	`0.00902229`	`0.00902229`
`methanol400`	`4.5550`	`6.9700`	`0.654`	`0.00902229`	`0.00902229`
`methanol50`	`0.0810`	`0.1600`	`0.506`	`0.00902229`	`0.00902229`
`minsurf100`	`0.5260`	`9.1700`	`0.057`	`2.50694962`	`2.50694962`
`minsurf25`	`0.1450`	`0.6500`	`0.223`	`2.51948798`	`2.51948798`
`minsurf50`	`0.2360`	`2.2900`	`0.103`	`2.51489003`	`2.51489003`
`minsurf75`	`1.3620`	`14.7400`	`0.092`	`2.50568661`	`2.50568709`
`pinene100`	`0.1680`	`0.4400`	`0.382`	`19.87217015`	`19.87217015`
`pinene200`	`0.4250`	`0.9100`	`0.467`	`19.87216684`	`19.87216684`
`pinene25`	`0.0810`	`0.2400`	`0.338`	`19.87216552`	`19.87216552`
`pinene50`	`0.0810`	`0.2600`	`0.312`	`19.87216552`	`19.87216552`
`polygon100`	`3.7980`	`5.0700`	`0.749`	`-0.78505614`	`-0.78505614`
`polygon25`	`0.0350`	`0.1000`	`0.350`	`-0.77974054`	`-0.77974054`
`polygon50`	`0.6580`	`1.5500`	`0.425`	`-0.78213256`	`-0.78213256`
`polygon75`	`2.8940`	`6.2900`	`0.460`	`-0.78446376`	`-0.78446376`
`popdynm100`	`0.2590`	`0.5100`	`0.508`	`19746.52860214`	`19746.52860214`
`popdynm200`	`0.6550`	`1.4100`	`0.465`	`19746.52964658`	`19746.52964658`
`popdynm25`	`0.0990`	`0.3200`	`0.309`	`19752.21541508`	`19752.21541508`
`popdynm50`	`0.1490`	`0.7200`	`0.207`	`19746.54515625`	`19746.54515625`
`robot100`	`6.4560`	`3600.1300`	---	`mstat( 3) sstat(1)`	`mstat( 6) sstat(3)`
`robot200`	`0.2740`	`0.8600`	`0.319`	`9.14139686`	`9.14139688`
`robot400`	`0.7520`	`2.6500`	`0.284`	`9.14102607`	`9.14102607`
`robot50`	`102.4360`	`43.2100`	---	`mstat( 6) sstat(4)`	`mstat( 3) sstat(1)`
`rocket100`	`1.8710`	`5.7200`	`0.327`	`-1.01283202`	`-1.01283202`
`rocket200`	`12.0200`	`33.5700`	`0.358`	`-1.01283569`	`-1.01283569`
`rocket400`	`118.6340`	`255.5200`	`0.464`	`-1.01283661`	`-1.01283661`
`torsion100`	`0.5540`	`13.6900`	`0.040`	`-0.41823920`	`-0.41823920`
`torsion25`	`0.1320`	`0.8600`	`0.153`	`-0.41751073`	`-0.41751073`
`torsion50`	`0.2660`	`3.6800`	`0.072`	`-0.41808762`	`-0.41808762`
`torsion75`	`0.4090`	`7.9600`	`0.051`	`-0.41819939`	`-0.41819939`