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 COINIPOPTDmumps 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-2.trc
Tracefile 2:	IPOPT-2.trc
Solvers used :	COINIPOPTDmumps
	IPOPTmumps
Modeltype(s)	`NLP`

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

COINIPOPTDmumps: optimal -- IPOPTmumps: locally optimal

Modelname	Time (COINIPOPTDmumps)	Time (IPOPTmumps)	Ratio (COINIPOPTDmumps/IPOPTmumps)	Obj (COINIPOPTDmumps)	Obj (IPOPTmumps)
`arki0018`	`1.1790`	`0.8300`	`1.420`	`0.01045662`	`0.01045662`
`arki0020`	`0.1410`	`0.2600`	`0.542`	`-41.07495436`	`-41.07495436`
`arki0021`	`0.4440`	`1.3700`	`0.324`	`-72.58210091`	`-72.58210091`
`arki0022`	`0.6890`	`2.4900`	`0.277`	`-87.09909127`	`-87.09909127`
`arki0023`	`1.4030`	`9.0600`	`0.155`	`-153.66007775`	`-153.66007775`
`jbearing100`	`0.6650`	`7.2100`	`0.092`	`-0.15504194`	`-0.15504194`
`jbearing25`	`0.1570`	`0.5800`	`0.271`	`-0.15401551`	`-0.15401551`
`jbearing50`	`0.3140`	`1.7700`	`0.177`	`-0.15482381`	`-0.15482381`
`jbearing75`	`0.4640`	`3.9800`	`0.117`	`-0.15498446`	`-0.15498446`
`minsurf100`	`0.6810`	`9.1700`	`0.074`	`2.50694962`	`2.50694962`
`minsurf25`	`0.1500`	`0.6500`	`0.231`	`2.51948798`	`2.51948798`
`minsurf50`	`0.3140`	`2.2900`	`0.137`	`2.51489003`	`2.51489003`
`minsurf75`	`2.1080`	`14.7400`	`0.143`	`2.50568721`	`2.50568709`

COINIPOPTDmumps: locally optimal -- IPOPTmumps: locally optimal

Modelname	Time (COINIPOPTDmumps)	Time (IPOPTmumps)	Ratio (COINIPOPTDmumps/IPOPTmumps)	Obj (COINIPOPTDmumps)	Obj (IPOPTmumps)
`arki0002`	`0.3200`	`0.2800`	`1.143`	`1.87252774`	`1.87252774`
`arki0004`	`3.5800`	`4.9200`	`0.728`	`327.73301341`	`327.73301341`
`arki0011`	`91.9100`	`115.0700`	`0.799`	`-224086.45997864`	`-224086.45996109`
`arki0012`	`89.9340`	`152.7100`	`0.589`	`-224252.27283280`	`-224252.44284664`
`arki0013`	`154.5390`	`119.2700`	`1.296`	`-224253.08721105`	`-224253.08150466`
`arki0014`	`135.2720`	`122.7900`	`1.102`	`-223977.06909780`	`-223977.07395310`
`arki0015`	`5.7990`	`5.4700`	`1.060`	`-266.94068809`	`-266.94068809`
`arki0016`	`15.8850`	`15.7500`	`1.009`	`867.97316601`	`867.97316601`
`arki0017`	`1.4140`	`1.4300`	`0.989`	`-121.83308011`	`-121.83308011`
`camshape400`	`1.2920`	`1.3200`	`0.979`	`-4.27569663`	`-4.27569663`
`camshape800`	`150.9280`	`167.6800`	`0.900`	`-4.27430687`	`-4.27430687`
`catmix100`	`0.0990`	`0.0600`	`1.650`	`-0.04806941`	`-0.04806941`
`catmix200`	`0.0840`	`0.0900`	`0.933`	`-0.04805914`	`-0.04805914`
`catmix400`	`0.1540`	`0.1400`	`1.100`	`-0.04805654`	`-0.04805654`
`catmix800`	`0.2660`	`0.2800`	`0.950`	`-0.04805590`	`-0.04805590`
`chain400`	`0.0600`	`0.0700`	`0.857`	`5.06862169`	`5.06862169`
`elec200`	`51.8720`	`1213.6100`	`0.043`	`18439.26774952`	`18439.26774952`
`ex8_2_2a`	`4.9920`	`4.4700`	`1.117`	`-552.66625903`	`-552.66625903`
`ex8_2_2b`	`6.8980`	`6.0400`	`1.142`	`-552.66625998`	`-552.66625998`
`ex8_2_3a`	`11.9870`	`10.6100`	`1.130`	`-3731.07929678`	`-3731.07929678`
`ex8_2_3b`	`13.8100`	`12.4600`	`1.108`	`-3731.07929695`	`-3731.07929695`
`ex8_2_5a`	`3.5250`	`3.4800`	`1.013`	`-830.33806763`	`-830.33806763`
`ex8_2_5b`	`10.1360`	`10.7900`	`0.939`	`-830.33806763`	`-830.33806763`
`flowchan100`	`0.1060`	`0.1000`	`1.060`	`0.00000000`	`0.00000000`
`flowchan200`	`0.2220`	`0.1900`	`1.168`	`0.00000000`	`0.00000000`
`flowchan400`	`0.8130`	`0.4100`	`1.983`	`0.00000000`	`0.00000000`
`gasoil100`	`0.4830`	`0.3800`	`1.271`	`0.00523659`	`0.00523659`
`gasoil200`	`0.7570`	`0.6800`	`1.113`	`0.00523660`	`0.00523660`
`gasoil400`	`1.7710`	`1.6100`	`1.100`	`0.00523660`	`0.00523660`
`gasoil50`	`0.1680`	`0.1500`	`1.120`	`0.00523664`	`0.00523664`
`infeas1`	`0.7690`	`0.7000`	`1.099`	`13685.59647017`	`13685.59647018`
`lnts100`	`0.3370`	`0.1100`	`3.064`	`0.55459540`	`0.55459540`
`lnts200`	`0.1380`	`0.1300`	`1.062`	`0.55457702`	`0.55457702`
`lnts400`	`0.2820`	`0.2600`	`1.085`	`0.55457241`	`0.55457241`
`methanol100`	`0.5090`	`0.5000`	`1.018`	`0.00902229`	`0.00902229`
`methanol200`	`5.2700`	`7.5500`	`0.698`	`0.00902229`	`0.00902229`
`methanol400`	`6.7100`	`6.9700`	`0.963`	`0.00902229`	`0.00902229`
`methanol50`	`0.1730`	`0.1600`	`1.081`	`0.00902229`	`0.00902229`
`pinene100`	`0.4800`	`0.4400`	`1.091`	`19.87217015`	`19.87217015`
`pinene200`	`1.0070`	`0.9100`	`1.107`	`19.87216684`	`19.87216684`
`pinene25`	`0.2610`	`0.2400`	`1.088`	`19.87216552`	`19.87216552`
`pinene50`	`0.2640`	`0.2600`	`1.015`	`19.87216552`	`19.87216552`
`polygon100`	`4.7510`	`5.0700`	`0.937`	`-0.78505614`	`-0.78505614`
`polygon25`	`0.1110`	`0.1000`	`1.110`	`-0.77974054`	`-0.77974054`
`polygon50`	`1.6330`	`1.5500`	`1.054`	`-0.78213256`	`-0.78213256`
`polygon75`	`6.1170`	`6.2900`	`0.972`	`-0.78446376`	`-0.78446376`
`popdynm100`	`0.5360`	`0.5100`	`1.051`	`19746.52860214`	`19746.52860214`
`popdynm200`	`1.3650`	`1.4100`	`0.968`	`19746.52964658`	`19746.52964658`
`popdynm25`	`0.2850`	`0.3200`	`0.891`	`19752.21541508`	`19752.21541508`
`popdynm50`	`0.8030`	`0.7200`	`1.115`	`19746.54515625`	`19746.54515625`
`robot200`	`0.8570`	`0.8600`	`0.997`	`9.14139688`	`9.14139688`
`robot400`	`2.6250`	`2.6500`	`0.991`	`9.14102607`	`9.14102607`
`rocket100`	`5.2810`	`5.7200`	`0.923`	`-1.01283202`	`-1.01283202`
`rocket200`	`31.9930`	`33.5700`	`0.953`	`-1.01283569`	`-1.01283569`
`rocket400`	`233.8110`	`255.5200`	`0.915`	`-1.01283661`	`-1.01283661`
`torsion100`	`0.7270`	`13.6900`	`0.053`	`-0.41823920`	`-0.41823920`
`torsion25`	`0.1620`	`0.8600`	`0.188`	`-0.41751073`	`-0.41751073`
`torsion50`	`0.3560`	`3.6800`	`0.097`	`-0.41808762`	`-0.41808762`
`torsion75`	`0.5350`	`7.9600`	`0.067`	`-0.41819939`	`-0.41819939`

COINIPOPTDmumps: locally optimal -- IPOPTmumps: infeasible

Modelname	Time (COINIPOPTDmumps)	Time (IPOPTmumps)	Ratio (COINIPOPTDmumps/IPOPTmumps)	Obj (COINIPOPTDmumps)	Status (IPOPTmumps)
`glider200`	`1821.6560`	`866.6800`	---	`-1248.89636213`	`mstat( 5)sstat( 1)`

COINIPOPTDmumps: feasible -- IPOPTmumps: unbounded

Modelname	Time (COINIPOPTDmumps)	Time (IPOPTmumps)	Ratio (COINIPOPTDmumps/IPOPTmumps)	Obj (COINIPOPTDmumps)	Status (IPOPTmumps)
`robot50`	`41.6870`	`43.2100`	---	`-1.5576010946900E+16`	`mstat( 3)sstat( 1)`

COINIPOPTDmumps: infeasible -- IPOPTmumps: infeasible

Modelname	Time (COINIPOPTDmumps)	Time (IPOPTmumps)	Ratio (COINIPOPTDmumps/IPOPTmumps)	Status (COINIPOPTDmumps)	Status (IPOPTmumps)
`glider100`	`2.1410`	`2.0800`	---	`mstat( 5)sstat( 1)`	`mstat( 5)sstat( 1)`
`glider400`	`7.9980`	`9.5100`	---	`mstat( 5)sstat( 1)`	`mstat( 5)sstat( 1)`
`glider50`	`0.8090`	`0.7800`	---	`mstat( 5)sstat( 1)`	`mstat( 5)sstat( 1)`

COINIPOPTDmumps: fail -- IPOPTmumps: fail

Modelname	Time (COINIPOPTDmumps)	Time (IPOPTmumps)	Ratio (COINIPOPTDmumps/IPOPTmumps)	Status (COINIPOPTDmumps)	Status (IPOPTmumps)
`arki0003`	`3622.7920`	`3600.1000`	---	`mstat( 6)sstat( 3)`	`mstat( 6)sstat( 3)`
`arki0008`	`740.6630`	`788.1100`	---	`mstat( 6)sstat( 4)`	`mstat( 6)sstat( 4)`
`ex8_2_2`	`NA`	`3637.2900`	---	`mstat(13)sstat(13)`	`mstat( 6)sstat( 3)`
`robot100`	`3638.1290`	`3600.1300`	---	`mstat( 6)sstat( 3)`	`mstat( 6)sstat( 3)`

COINIPOPTDmumps: optimal:

Modelname	Time (COINIPOPTDmumps)	Obj (COINIPOPTDmumps)
`arki0018`	`1.1790`	`0.01045662`
`arki0020`	`0.1410`	`-41.07495436`
`arki0021`	`0.4440`	`-72.58210091`
`arki0022`	`0.6890`	`-87.09909127`
`arki0023`	`1.4030`	`-153.66007775`
`jbearing100`	`0.6650`	`-0.15504194`
`jbearing25`	`0.1570`	`-0.15401551`
`jbearing50`	`0.3140`	`-0.15482381`
`jbearing75`	`0.4640`	`-0.15498446`
`minsurf100`	`0.6810`	`2.50694962`
`minsurf25`	`0.1500`	`2.51948798`
`minsurf50`	`0.3140`	`2.51489003`
`minsurf75`	`2.1080`	`2.50568721`

COINIPOPTDmumps: locally optimal:

Modelname	Time (COINIPOPTDmumps)	Obj (COINIPOPTDmumps)
`arki0002`	`0.3200`	`1.87252774`
`arki0004`	`3.5800`	`327.73301341`
`arki0011`	`91.9100`	`-224086.45997864`
`arki0012`	`89.9340`	`-224252.27283280`
`arki0013`	`154.5390`	`-224253.08721105`
`arki0014`	`135.2720`	`-223977.06909780`
`arki0015`	`5.7990`	`-266.94068809`
`arki0016`	`15.8850`	`867.97316601`
`arki0017`	`1.4140`	`-121.83308011`
`camshape400`	`1.2920`	`-4.27569663`
`camshape800`	`150.9280`	`-4.27430687`
`catmix100`	`0.0990`	`-0.04806941`
`catmix200`	`0.0840`	`-0.04805914`
`catmix400`	`0.1540`	`-0.04805654`
`catmix800`	`0.2660`	`-0.04805590`
`chain400`	`0.0600`	`5.06862169`
`elec200`	`51.8720`	`18439.26774952`
`ex8_2_2a`	`4.9920`	`-552.66625903`
`ex8_2_2b`	`6.8980`	`-552.66625998`
`ex8_2_3a`	`11.9870`	`-3731.07929678`
`ex8_2_3b`	`13.8100`	`-3731.07929695`
`ex8_2_5a`	`3.5250`	`-830.33806763`
`ex8_2_5b`	`10.1360`	`-830.33806763`
`flowchan100`	`0.1060`	`0.00000000`
`flowchan200`	`0.2220`	`0.00000000`
`flowchan400`	`0.8130`	`0.00000000`
`gasoil100`	`0.4830`	`0.00523659`
`gasoil200`	`0.7570`	`0.00523660`
`gasoil400`	`1.7710`	`0.00523660`
`gasoil50`	`0.1680`	`0.00523664`
`glider200`	`1821.6560`	`-1248.89636213`
`infeas1`	`0.7690`	`13685.59647017`
`lnts100`	`0.3370`	`0.55459540`
`lnts200`	`0.1380`	`0.55457702`
`lnts400`	`0.2820`	`0.55457241`
`methanol100`	`0.5090`	`0.00902229`
`methanol200`	`5.2700`	`0.00902229`
`methanol400`	`6.7100`	`0.00902229`
`methanol50`	`0.1730`	`0.00902229`
`pinene100`	`0.4800`	`19.87217015`
`pinene200`	`1.0070`	`19.87216684`
`pinene25`	`0.2610`	`19.87216552`
`pinene50`	`0.2640`	`19.87216552`
`polygon100`	`4.7510`	`-0.78505614`
`polygon25`	`0.1110`	`-0.77974054`
`polygon50`	`1.6330`	`-0.78213256`
`polygon75`	`6.1170`	`-0.78446376`
`popdynm100`	`0.5360`	`19746.52860214`
`popdynm200`	`1.3650`	`19746.52964658`
`popdynm25`	`0.2850`	`19752.21541508`
`popdynm50`	`0.8030`	`19746.54515625`
`robot200`	`0.8570`	`9.14139688`
`robot400`	`2.6250`	`9.14102607`
`rocket100`	`5.2810`	`-1.01283202`
`rocket200`	`31.9930`	`-1.01283569`
`rocket400`	`233.8110`	`-1.01283661`
`torsion100`	`0.7270`	`-0.41823920`
`torsion25`	`0.1620`	`-0.41751073`
`torsion50`	`0.3560`	`-0.41808762`
`torsion75`	`0.5350`	`-0.41819939`

COINIPOPTDmumps: feasible:

Modelname	Time (COINIPOPTDmumps)	Obj (COINIPOPTDmumps)
`robot50`	`41.6870`	`-1.5576010946900E+16`

COINIPOPTDmumps: infeasible:

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

COINIPOPTDmumps: fail:

Modelname	Time (COINIPOPTDmumps)	Status (COINIPOPTDmumps)
`arki0003`	`--`	`mstat( 6) sstat( 3)`
`arki0008`	`--`	`mstat( 6) sstat( 4)`
`ex8_2_2`	`--`	`mstat(13) sstat(13)`
`robot100`	`--`	`mstat( 6) sstat( 3)`

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)`

COINIPOPTDmumps: all -- IPOPTmumps: all

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

Modelname	Time (COINIPOPTDmumps)	Time (IPOPTmumps)	Ratio (COINIPOPTDmumps/ IPOPTmumps)	Obj (COINIPOPTDmumps)	Obj (IPOPTmumps)
`arki0002`	`0.3200`	`0.2800`	`1.143`	`1.87252774`	`1.87252774`
`arki0003`	`3622.7920`	`3600.1000`	---	`mstat( 6) sstat(3)`	`mstat( 6) sstat(3)`
`arki0004`	`3.5800`	`4.9200`	`0.728`	`327.73301341`	`327.73301341`
`arki0008`	`740.6630`	`788.1100`	---	`mstat( 6) sstat(4)`	`mstat( 6) sstat(4)`
`arki0011`	`91.9100`	`115.0700`	`0.799`	`-224086.45997864`	`-224086.45996109`
`arki0012`	`89.9340`	`152.7100`	`0.589`	`-224252.27283280`	`-224252.44284664`
`arki0013`	`154.5390`	`119.2700`	`1.296`	`-224253.08721105`	`-224253.08150466`
`arki0014`	`135.2720`	`122.7900`	`1.102`	`-223977.06909780`	`-223977.07395310`
`arki0015`	`5.7990`	`5.4700`	`1.060`	`-266.94068809`	`-266.94068809`
`arki0016`	`15.8850`	`15.7500`	`1.009`	`867.97316601`	`867.97316601`
`arki0017`	`1.4140`	`1.4300`	`0.989`	`-121.83308011`	`-121.83308011`
`arki0018`	`1.1790`	`0.8300`	`1.420`	`0.01045662`	`0.01045662`
`arki0020`	`0.1410`	`0.2600`	`0.542`	`-41.07495436`	`-41.07495436`
`arki0021`	`0.4440`	`1.3700`	`0.324`	`-72.58210091`	`-72.58210091`
`arki0022`	`0.6890`	`2.4900`	`0.277`	`-87.09909127`	`-87.09909127`
`arki0023`	`1.4030`	`9.0600`	`0.155`	`-153.66007775`	`-153.66007775`
`camshape400`	`1.2920`	`1.3200`	`0.979`	`-4.27569663`	`-4.27569663`
`camshape800`	`150.9280`	`167.6800`	`0.900`	`-4.27430687`	`-4.27430687`
`catmix100`	`0.0990`	`0.0600`	`1.650`	`-0.04806941`	`-0.04806941`
`catmix200`	`0.0840`	`0.0900`	`0.933`	`-0.04805914`	`-0.04805914`
`catmix400`	`0.1540`	`0.1400`	`1.100`	`-0.04805654`	`-0.04805654`
`catmix800`	`0.2660`	`0.2800`	`0.950`	`-0.04805590`	`-0.04805590`
`chain400`	`0.0600`	`0.0700`	`0.857`	`5.06862169`	`5.06862169`
`elec200`	`51.8720`	`1213.6100`	`0.043`	`18439.26774952`	`18439.26774952`
`ex8_2_2`	`NA`	`3637.2900`	---	`mstat(13) sstat(13)`	`mstat( 6) sstat(3)`
`ex8_2_2a`	`4.9920`	`4.4700`	`1.117`	`-552.66625903`	`-552.66625903`
`ex8_2_2b`	`6.8980`	`6.0400`	`1.142`	`-552.66625998`	`-552.66625998`
`ex8_2_3a`	`11.9870`	`10.6100`	`1.130`	`-3731.07929678`	`-3731.07929678`
`ex8_2_3b`	`13.8100`	`12.4600`	`1.108`	`-3731.07929695`	`-3731.07929695`
`ex8_2_5a`	`3.5250`	`3.4800`	`1.013`	`-830.33806763`	`-830.33806763`
`ex8_2_5b`	`10.1360`	`10.7900`	`0.939`	`-830.33806763`	`-830.33806763`
`flowchan100`	`0.1060`	`0.1000`	`1.060`	`0.00000000`	`0.00000000`
`flowchan200`	`0.2220`	`0.1900`	`1.168`	`0.00000000`	`0.00000000`
`flowchan400`	`0.8130`	`0.4100`	`1.983`	`0.00000000`	`0.00000000`
`gasoil100`	`0.4830`	`0.3800`	`1.271`	`0.00523659`	`0.00523659`
`gasoil200`	`0.7570`	`0.6800`	`1.113`	`0.00523660`	`0.00523660`
`gasoil400`	`1.7710`	`1.6100`	`1.100`	`0.00523660`	`0.00523660`
`gasoil50`	`0.1680`	`0.1500`	`1.120`	`0.00523664`	`0.00523664`
`glider100`	`2.1410`	`2.0800`	---	`mstat( 5) sstat(1)`	`mstat( 5) sstat(1)`
`glider200`	`1821.6560`	`866.6800`	---	`-1248.89636213`	`mstat( 5) sstat(1)`
`glider400`	`7.9980`	`9.5100`	---	`mstat( 5) sstat(1)`	`mstat( 5) sstat(1)`
`glider50`	`0.8090`	`0.7800`	---	`mstat( 5) sstat(1)`	`mstat( 5) sstat(1)`
`infeas1 (max)`	`0.7690`	`0.7000`	`1.099`	`13685.59647017`	`13685.59647018`
`jbearing100`	`0.6650`	`7.2100`	`0.092`	`-0.15504194`	`-0.15504194`
`jbearing25`	`0.1570`	`0.5800`	`0.271`	`-0.15401551`	`-0.15401551`
`jbearing50`	`0.3140`	`1.7700`	`0.177`	`-0.15482381`	`-0.15482381`
`jbearing75`	`0.4640`	`3.9800`	`0.117`	`-0.15498446`	`-0.15498446`
`lnts100`	`0.3370`	`0.1100`	`3.064`	`0.55459540`	`0.55459540`
`lnts200`	`0.1380`	`0.1300`	`1.062`	`0.55457702`	`0.55457702`
`lnts400`	`0.2820`	`0.2600`	`1.085`	`0.55457241`	`0.55457241`
`methanol100`	`0.5090`	`0.5000`	`1.018`	`0.00902229`	`0.00902229`
`methanol200`	`5.2700`	`7.5500`	`0.698`	`0.00902229`	`0.00902229`
`methanol400`	`6.7100`	`6.9700`	`0.963`	`0.00902229`	`0.00902229`
`methanol50`	`0.1730`	`0.1600`	`1.081`	`0.00902229`	`0.00902229`
`minsurf100`	`0.6810`	`9.1700`	`0.074`	`2.50694962`	`2.50694962`
`minsurf25`	`0.1500`	`0.6500`	`0.231`	`2.51948798`	`2.51948798`
`minsurf50`	`0.3140`	`2.2900`	`0.137`	`2.51489003`	`2.51489003`
`minsurf75`	`2.1080`	`14.7400`	`0.143`	`2.50568721`	`2.50568709`
`pinene100`	`0.4800`	`0.4400`	`1.091`	`19.87217015`	`19.87217015`
`pinene200`	`1.0070`	`0.9100`	`1.107`	`19.87216684`	`19.87216684`
`pinene25`	`0.2610`	`0.2400`	`1.088`	`19.87216552`	`19.87216552`
`pinene50`	`0.2640`	`0.2600`	`1.015`	`19.87216552`	`19.87216552`
`polygon100`	`4.7510`	`5.0700`	`0.937`	`-0.78505614`	`-0.78505614`
`polygon25`	`0.1110`	`0.1000`	`1.110`	`-0.77974054`	`-0.77974054`
`polygon50`	`1.6330`	`1.5500`	`1.054`	`-0.78213256`	`-0.78213256`
`polygon75`	`6.1170`	`6.2900`	`0.972`	`-0.78446376`	`-0.78446376`
`popdynm100`	`0.5360`	`0.5100`	`1.051`	`19746.52860214`	`19746.52860214`
`popdynm200`	`1.3650`	`1.4100`	`0.968`	`19746.52964658`	`19746.52964658`
`popdynm25`	`0.2850`	`0.3200`	`0.891`	`19752.21541508`	`19752.21541508`
`popdynm50`	`0.8030`	`0.7200`	`1.115`	`19746.54515625`	`19746.54515625`
`robot100`	`3638.1290`	`3600.1300`	---	`mstat( 6) sstat(3)`	`mstat( 6) sstat(3)`
`robot200`	`0.8570`	`0.8600`	`0.997`	`9.14139688`	`9.14139688`
`robot400`	`2.6250`	`2.6500`	`0.991`	`9.14102607`	`9.14102607`
`robot50`	`41.6870`	`43.2100`	---	`-1.5576010946900E+16`	`mstat( 3) sstat(1)`
`rocket100`	`5.2810`	`5.7200`	`0.923`	`-1.01283202`	`-1.01283202`
`rocket200`	`31.9930`	`33.5700`	`0.953`	`-1.01283569`	`-1.01283569`
`rocket400`	`233.8110`	`255.5200`	`0.915`	`-1.01283661`	`-1.01283661`
`torsion100`	`0.7270`	`13.6900`	`0.053`	`-0.41823920`	`-0.41823920`
`torsion25`	`0.1620`	`0.8600`	`0.188`	`-0.41751073`	`-0.41751073`
`torsion50`	`0.3560`	`3.6800`	`0.097`	`-0.41808762`	`-0.41808762`
`torsion75`	`0.5350`	`7.9600`	`0.067`	`-0.41819939`	`-0.41819939`