Solver Square Comparison

Solver Square Comparison: Considers all models.

Date / Time: 10/19/08 15:15:26

Solver comparison utility.

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 IPOPTMUMPS 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.

Tracefile 1 :	`IPOPT-2.trc`
Tracefile 2 :	`CONOPT-1.trc`
Solvers used :	`IPOPTMUMPS`
	`CONOPT`
Modeltype(s)	`NLP`

	CONOPT: optimal	CONOPT: locally optimal	CONOPT: feasible	CONOPT: infeasible	CONOPT: unbounded	CONOPT: fail	CONOPT: no data	total IPOPTMUMPS
IPOPTMUMPS: optimal	-	-	-	-	-	-	-	`-`
IPOPTMUMPS: locally optimal	-	`71`	-	-	-	`3`	-	`74`
IPOPTMUMPS: feasible	-	`1`	-	`1`	-	-	-	`2`
IPOPTMUMPS: infeasible	-	`1`	-	`1`	-	-	-	`2`
IPOPTMUMPS: unbounded	-	-	-	-	-	-	-	`-`
IPOPTMUMPS: fail	-	`1`	-	`1`	`1`	-	-	`3`
IPOPTMUMPS: no data	-	-	-	-	-	-	-	`-`
total CONOPT	`-`	`74`	`-`	`3`	`1`	`3`	`-`	`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 5.00E-03. 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.

IPOPTMUMPS: locally optimal -- CONOPT: locally optimal Back to top

Modelname	Time (IPOPTMUMPS)	Time (CONOPT)	Ratio (IPOPTMUMPS/CONOPT)	Obj (IPOPTMUMPS)	Obj (CONOPT)
`arki0002`	`0.5000`	`1.4000`	`0.357`	`1.87252774`	`1.09905910`
`arki0003`	`110.0500`	`12.1100`	`9.088`	`3795.20606793`	`3795.20606459`
`arki0004`	`5.8300`	`1.3800`	`4.225`	`327.73301341`	`323.46703883`
`arki0011`	`105.3900`	`7.8000`	`13.512`	`-224086.45997466`	`-224086.46003881`
`arki0012`	`172.9100`	`1016.2100`	`0.170`	`-224252.44185188`	`-224252.44569385`
`arki0015`	`9.0400`	`1.0600`	`8.528`	`-266.94068809`	`-271.73572350`
`arki0016`	`4.4500`	`843.3200`	`0.005`	`867.97316601`	`867.97316601`
`arki0017`	`3.5100`	`99.6400`	`0.035`	`-121.83308010`	`-121.83308010`
`arki0018`	`1.2200`	`1.5400`	`0.792`	`0.01045662`	`0.01045662`
`arki0020`	`0.5100`	`3.2100`	`0.159`	`-41.07495436`	`-41.07495436`
`arki0021`	`2.1100`	`81.8800`	`0.026`	`-72.58210091`	`-72.58210091`
`arki0022`	`5.2600`	`73.4400`	`0.072`	`-87.09909127`	`-87.09909127`
`arki0023`	`13.6100`	`14.2000`	`0.958`	`-153.66007775`	`-153.66007775`
`camshape400`	`0.9200`	`0.0800`	`11.500`	`-4.27568847`	`-4.27568848`
`camshape800`	`1.6700`	`0.3200`	`5.219`	`-4.27427413`	`-4.27427414`
`catmix100`	`0.1600`	`0.0800`	`2.000`	`-0.04806941`	`-0.04806939`
`catmix200`	`0.1800`	`0.0900`	`2.000`	`-0.04805914`	`-0.04805914`
`catmix400`	`0.4900`	`0.2300`	`2.130`	`-0.04805654`	`-0.04805654`
`catmix800`	`0.8000`	`0.7300`	`1.096`	`-0.04805590`	`-0.04805590`
`chain400`	`0.1500`	`0.2000`	`0.750`	`5.06862169`	`5.06862169`
`elec200`	`1473.1900`	`29.0300`	`50.747`	`18439.26774952`	`18438.99952062`
`ex8_2_2a`	`8.3800`	`8.7700`	`0.956`	`-552.66625860`	`-552.66625940`
`ex8_2_2b`	`12.9500`	`7.7900`	`1.662`	`-552.66625954`	`-552.66625902`
`ex8_2_3a`	`17.8100`	`17.7600`	`1.003`	`-3731.07929639`	`-3731.07929542`
`ex8_2_3b`	`20.0300`	`16.0800`	`1.246`	`-3731.07929656`	`-3731.07929509`
`ex8_2_5a`	`7.8200`	`4.4100`	`1.773`	`-830.33806724`	`-830.33806698`
`ex8_2_5b`	`15.4100`	`3.2100`	`4.801`	`-830.33806724`	`-830.33806699`
`flowchan100`	`0.2600`	`0.0600`	`4.333`	`0.00000000`	`0.00000000`
`flowchan200`	`0.4200`	`0.1300`	`3.231`	`0.00000000`	`0.00000000`
`flowchan400`	`0.7200`	`0.7000`	`1.029`	`0.00000000`	`0.00000000`
`gasoil100`	`1.0100`	`0.3400`	`2.971`	`0.00523659`	`0.00523659`
`gasoil200`	`1.1600`	`0.5000`	`2.320`	`0.00523660`	`0.00523660`
`gasoil400`	`2.7300`	`1.5000`	`1.820`	`0.00523660`	`0.00523660`
`gasoil50`	`0.3900`	`0.1700`	`2.294`	`0.00523664`	`0.00523664`
`glider400`	`43.4900`	`528.6400`	`0.082`	`-250.00000000`	`-1247.97431754`
`infeas1`	`1.1000`	`0.3600`	`3.056`	`13685.59646092`	`13685.59646095`
`jbearing100`	`9.1900`	`76.1000`	`0.121`	`-0.15504194`	`-0.15504196`
`jbearing25`	`1.1300`	`2.3700`	`0.477`	`-0.15401551`	`-0.15401554`
`jbearing50`	`2.3800`	`14.0100`	`0.170`	`-0.15482381`	`-0.15482422`
`jbearing75`	`5.5400`	`36.2300`	`0.153`	`-0.15498446`	`-0.15498453`
`lnts100`	`0.1900`	`0.1900`	`1.000`	`0.55459540`	`0.55459540`
`lnts200`	`0.2700`	`0.7400`	`0.365`	`0.55457702`	`0.55457702`
`lnts400`	`0.4500`	`1.9100`	`0.236`	`0.55457241`	`0.55457241`
`methanol100`	`1.2000`	`0.3200`	`3.750`	`0.00902229`	`0.00902229`
`methanol200`	`7.5900`	`0.6600`	`11.500`	`0.00902229`	`0.00902229`
`methanol400`	`10.3000`	`1.4800`	`6.959`	`0.00902229`	`0.00902229`
`methanol50`	`0.2900`	`0.1600`	`1.812`	`0.00902229`	`0.00902229`
`minsurf100`	`11.5400`	`78.2400`	`0.147`	`2.50694962`	`2.50694926`
`minsurf25`	`1.2400`	`1.3700`	`0.905`	`2.51948798`	`2.51948768`
`minsurf50`	`3.4100`	`12.0200`	`0.284`	`2.51489003`	`2.51488916`
`minsurf75`	`19.0600`	`37.2700`	`0.511`	`2.50568704`	`2.50568648`
`pinene100`	`1.0300`	`0.4400`	`2.341`	`19.87217015`	`19.87217015`
`pinene200`	`2.0900`	`1.4400`	`1.451`	`19.87216684`	`19.87216684`
`pinene25`	`0.5800`	`0.2800`	`2.071`	`19.87216552`	`19.87216552`
`pinene50`	`0.3800`	`0.2700`	`1.407`	`19.87216552`	`19.87216552`
`polygon100`	`7.7700`	`9.9600`	`0.780`	`-0.78505614`	`-0.78489329`
`polygon25`	`0.1400`	`0.3100`	`0.452`	`-0.77974054`	`-0.77914600`
`polygon50`	`2.1100`	`0.8800`	`2.398`	`-0.78213256`	`-0.78281345`
`polygon75`	`7.3300`	`4.5700`	`1.604`	`-0.78446376`	`-0.78367803`
`popdynm100`	`0.9100`	`5.0100`	`0.182`	`19746.52860217`	`19746.52860217`
`popdynm200`	`3.6300`	`10.3700`	`0.350`	`19746.52964660`	`19746.52964660`
`popdynm25`	`0.4900`	`0.7800`	`0.628`	`19752.21541511`	`19752.21541511`
`popdynm50`	`0.7600`	`2.1400`	`0.355`	`19746.54515628`	`19746.54515628`
`robot200`	`1.1600`	`1.1400`	`1.018`	`9.14139688`	`9.14139550`
`robot400`	`3.0100`	`2.8300`	`1.064`	`9.14102607`	`9.14102603`
`rocket100`	`0.7000`	`0.9500`	`0.737`	`-1.01283201`	`-1.01283202`
`rocket200`	`2.4100`	`4.1900`	`0.575`	`-1.01283568`	`-1.01283569`
`torsion100`	`17.3900`	`68.0400`	`0.256`	`-0.41823920`	`-0.41823921`
`torsion25`	`1.2200`	`1.4700`	`0.830`	`-0.41751073`	`-0.41751073`
`torsion50`	`6.9400`	`10.1500`	`0.684`	`-0.41808762`	`-0.41808763`
`torsion75`	`10.1800`	`37.2400`	`0.273`	`-0.41819939`	`-0.41819940`

IPOPTMUMPS: locally optimal -- CONOPT: fail Back to top

Modelname	Time (IPOPTMUMPS)	Time (CONOPT)	Ratio (IPOPTMUMPS/CONOPT)	Obj (IPOPTMUMPS)	Status (CONOPT)
`arki0013`	`148.0000`	`19.8300`	---	`-224253.08813525`	`mstat( 6) sstat( 4)`
`arki0014`	`109.5500`	`25.4900`	---	`-223976.86141185`	`mstat( 6) sstat( 4)`
`rocket400`	`3.0800`	`4.1800`	---	`-1.01283661`	`mstat( 6) sstat( 4)`

IPOPTMUMPS: feasible -- CONOPT: locally optimal Back to top

Modelname	Time (IPOPTMUMPS)	Time (CONOPT)	Ratio (IPOPTMUMPS/CONOPT)	Obj (IPOPTMUMPS)	Obj (CONOPT)
`robot100`	`3600.0400`	`0.2800`	`12857.286`	`-2.2709461441873E+16`	`9.14268538`

IPOPTMUMPS: feasible -- CONOPT: infeasible Back to top

Modelname	Time (IPOPTMUMPS)	Time (CONOPT)	Ratio (IPOPTMUMPS/CONOPT)	Obj (IPOPTMUMPS)	Status (CONOPT)
`glider100`	`8.7200`	`3.8900`	---	`-250.00000000`	`mstat( 5) sstat( 1)`

IPOPTMUMPS: infeasible -- CONOPT: locally optimal Back to top

Modelname	Time (IPOPTMUMPS)	Time (CONOPT)	Ratio (IPOPTMUMPS/CONOPT)	Status (IPOPTMUMPS)	Obj (CONOPT)
`glider50`	`1.4800`	`12.2400`	---	`mstat( 5) sstat( 1)`	`-1286.97737315`

IPOPTMUMPS: infeasible -- CONOPT: infeasible Back to top

Modelname	Time (IPOPTMUMPS)	Time (CONOPT)	Ratio (IPOPTMUMPS/CONOPT)	Status (IPOPTMUMPS)	Status (CONOPT)
`glider200`	`13.4600`	`11.3900`	---	`mstat( 5) sstat( 1)`	`mstat( 5) sstat( 1)`

IPOPTMUMPS: fail -- CONOPT: locally optimal Back to top

Modelname	Time (IPOPTMUMPS)	Time (CONOPT)	Ratio (IPOPTMUMPS/CONOPT)	Status (IPOPTMUMPS)	Obj (CONOPT)
`robot50`	`3600.0100`	`0.1700`	---	`mstat( 6) sstat( 3)`	`9.14687850`

IPOPTMUMPS: fail -- CONOPT: infeasible Back to top

Modelname	Time (IPOPTMUMPS)	Time (CONOPT)	Ratio (IPOPTMUMPS/CONOPT)	Status (IPOPTMUMPS)	Status (CONOPT)
`arki0008`	`133.3600`	`26.0900`	---	`mstat( 6) sstat( 4)`	`mstat( 5) sstat( 1)`

IPOPTMUMPS: fail -- CONOPT: unbounded Back to top

Modelname	Time (IPOPTMUMPS)	Time (CONOPT)	Ratio (IPOPTMUMPS/CONOPT)	Status (IPOPTMUMPS)	Status (CONOPT)
`ex8_2_2`	`3630.9100`	`3.4400`	---	`mstat( 6) sstat( 3)`	`mstat( 3) sstat( 1)`

IPOPTMUMPS: locally optimal: Back to top

Modelname	Time (IPOPTMUMPS)	Obj (IPOPTMUMPS)
`arki0002`	`0.5000`	`1.87252774`
`arki0003`	`110.0500`	`3795.20606793`
`arki0004`	`5.8300`	`327.73301341`
`arki0011`	`105.3900`	`-224086.45997466`
`arki0012`	`172.9100`	`-224252.44185188`
`arki0013`	`148.0000`	`-224253.08813525`
`arki0014`	`109.5500`	`-223976.86141185`
`arki0015`	`9.0400`	`-266.94068809`
`arki0016`	`4.4500`	`867.97316601`
`arki0017`	`3.5100`	`-121.83308010`
`arki0018`	`1.2200`	`0.01045662`
`arki0020`	`0.5100`	`-41.07495436`
`arki0021`	`2.1100`	`-72.58210091`
`arki0022`	`5.2600`	`-87.09909127`
`arki0023`	`13.6100`	`-153.66007775`
`camshape400`	`0.9200`	`-4.27568847`
`camshape800`	`1.6700`	`-4.27427413`
`catmix100`	`0.1600`	`-0.04806941`
`catmix200`	`0.1800`	`-0.04805914`
`catmix400`	`0.4900`	`-0.04805654`
`catmix800`	`0.8000`	`-0.04805590`
`chain400`	`0.1500`	`5.06862169`
`elec200`	`1473.1900`	`18439.26774952`
`ex8_2_2a`	`8.3800`	`-552.66625860`
`ex8_2_2b`	`12.9500`	`-552.66625954`
`ex8_2_3a`	`17.8100`	`-3731.07929639`
`ex8_2_3b`	`20.0300`	`-3731.07929656`
`ex8_2_5a`	`7.8200`	`-830.33806724`
`ex8_2_5b`	`15.4100`	`-830.33806724`
`flowchan100`	`0.2600`	`0.00000000`
`flowchan200`	`0.4200`	`0.00000000`
`flowchan400`	`0.7200`	`0.00000000`
`gasoil100`	`1.0100`	`0.00523659`
`gasoil200`	`1.1600`	`0.00523660`
`gasoil400`	`2.7300`	`0.00523660`
`gasoil50`	`0.3900`	`0.00523664`
`glider400`	`43.4900`	`-250.00000000`
`infeas1`	`1.1000`	`13685.59646092`
`jbearing100`	`9.1900`	`-0.15504194`
`jbearing25`	`1.1300`	`-0.15401551`
`jbearing50`	`2.3800`	`-0.15482381`
`jbearing75`	`5.5400`	`-0.15498446`
`lnts100`	`0.1900`	`0.55459540`
`lnts200`	`0.2700`	`0.55457702`
`lnts400`	`0.4500`	`0.55457241`
`methanol100`	`1.2000`	`0.00902229`
`methanol200`	`7.5900`	`0.00902229`
`methanol400`	`10.3000`	`0.00902229`
`methanol50`	`0.2900`	`0.00902229`
`minsurf100`	`11.5400`	`2.50694962`
`minsurf25`	`1.2400`	`2.51948798`
`minsurf50`	`3.4100`	`2.51489003`
`minsurf75`	`19.0600`	`2.50568704`
`pinene100`	`1.0300`	`19.87217015`
`pinene200`	`2.0900`	`19.87216684`
`pinene25`	`0.5800`	`19.87216552`
`pinene50`	`0.3800`	`19.87216552`
`polygon100`	`7.7700`	`-0.78505614`
`polygon25`	`0.1400`	`-0.77974054`
`polygon50`	`2.1100`	`-0.78213256`
`polygon75`	`7.3300`	`-0.78446376`
`popdynm100`	`0.9100`	`19746.52860217`
`popdynm200`	`3.6300`	`19746.52964660`
`popdynm25`	`0.4900`	`19752.21541511`
`popdynm50`	`0.7600`	`19746.54515628`
`robot200`	`1.1600`	`9.14139688`
`robot400`	`3.0100`	`9.14102607`
`rocket100`	`0.7000`	`-1.01283201`
`rocket200`	`2.4100`	`-1.01283568`
`rocket400`	`3.0800`	`-1.01283661`
`torsion100`	`17.3900`	`-0.41823920`
`torsion25`	`1.2200`	`-0.41751073`
`torsion50`	`6.9400`	`-0.41808762`
`torsion75`	`10.1800`	`-0.41819939`

IPOPTMUMPS: feasible: Back to top

Modelname	Time (IPOPTMUMPS)	Obj (IPOPTMUMPS)
`glider100`	`8.7200`	`-250.00000000`
`robot100`	`3600.0400`	`-2.2709461441873E+16`

IPOPTMUMPS: infeasible: Back to top

Modelname	Time (IPOPTMUMPS)	Status (IPOPTMUMPS)
`glider200`	`--`	`mstat( 5) sstat( 1)`
`glider50`	`--`	`mstat( 5) sstat( 1)`

IPOPTMUMPS: fail: Back to top

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

CONOPT: locally optimal: Back to top

Modelname	Time (CONOPT)	Obj (CONOPT)
`arki0002`	`1.4000`	`1.09905910`
`arki0003`	`12.1100`	`3795.20606459`
`arki0004`	`1.3800`	`323.46703883`
`arki0011`	`7.8000`	`-224086.46003881`
`arki0012`	`1016.2100`	`-224252.44569385`
`arki0015`	`1.0600`	`-271.73572350`
`arki0016`	`843.3200`	`867.97316601`
`arki0017`	`99.6400`	`-121.83308010`
`arki0018`	`1.5400`	`0.01045662`
`arki0020`	`3.2100`	`-41.07495436`
`arki0021`	`81.8800`	`-72.58210091`
`arki0022`	`73.4400`	`-87.09909127`
`arki0023`	`14.2000`	`-153.66007775`
`camshape400`	`0.0800`	`-4.27568848`
`camshape800`	`0.3200`	`-4.27427414`
`catmix100`	`0.0800`	`-0.04806939`
`catmix200`	`0.0900`	`-0.04805914`
`catmix400`	`0.2300`	`-0.04805654`
`catmix800`	`0.7300`	`-0.04805590`
`chain400`	`0.2000`	`5.06862169`
`elec200`	`29.0300`	`18438.99952062`
`ex8_2_2a`	`8.7700`	`-552.66625940`
`ex8_2_2b`	`7.7900`	`-552.66625902`
`ex8_2_3a`	`17.7600`	`-3731.07929542`
`ex8_2_3b`	`16.0800`	`-3731.07929509`
`ex8_2_5a`	`4.4100`	`-830.33806698`
`ex8_2_5b`	`3.2100`	`-830.33806699`
`flowchan100`	`0.0600`	`0.00000000`
`flowchan200`	`0.1300`	`0.00000000`
`flowchan400`	`0.7000`	`0.00000000`
`gasoil100`	`0.3400`	`0.00523659`
`gasoil200`	`0.5000`	`0.00523660`
`gasoil400`	`1.5000`	`0.00523660`
`gasoil50`	`0.1700`	`0.00523664`
`glider400`	`528.6400`	`-1247.97431754`
`glider50`	`12.2400`	`-1286.97737315`
`infeas1`	`0.3600`	`13685.59646095`
`jbearing100`	`76.1000`	`-0.15504196`
`jbearing25`	`2.3700`	`-0.15401554`
`jbearing50`	`14.0100`	`-0.15482422`
`jbearing75`	`36.2300`	`-0.15498453`
`lnts100`	`0.1900`	`0.55459540`
`lnts200`	`0.7400`	`0.55457702`
`lnts400`	`1.9100`	`0.55457241`
`methanol100`	`0.3200`	`0.00902229`
`methanol200`	`0.6600`	`0.00902229`
`methanol400`	`1.4800`	`0.00902229`
`methanol50`	`0.1600`	`0.00902229`
`minsurf100`	`78.2400`	`2.50694926`
`minsurf25`	`1.3700`	`2.51948768`
`minsurf50`	`12.0200`	`2.51488916`
`minsurf75`	`37.2700`	`2.50568648`
`pinene100`	`0.4400`	`19.87217015`
`pinene200`	`1.4400`	`19.87216684`
`pinene25`	`0.2800`	`19.87216552`
`pinene50`	`0.2700`	`19.87216552`
`polygon100`	`9.9600`	`-0.78489329`
`polygon25`	`0.3100`	`-0.77914600`
`polygon50`	`0.8800`	`-0.78281345`
`polygon75`	`4.5700`	`-0.78367803`
`popdynm100`	`5.0100`	`19746.52860217`
`popdynm200`	`10.3700`	`19746.52964660`
`popdynm25`	`0.7800`	`19752.21541511`
`popdynm50`	`2.1400`	`19746.54515628`
`robot100`	`0.2800`	`9.14268538`
`robot200`	`1.1400`	`9.14139550`
`robot400`	`2.8300`	`9.14102603`
`robot50`	`0.1700`	`9.14687850`
`rocket100`	`0.9500`	`-1.01283202`
`rocket200`	`4.1900`	`-1.01283569`
`torsion100`	`68.0400`	`-0.41823921`
`torsion25`	`1.4700`	`-0.41751073`
`torsion50`	`10.1500`	`-0.41808763`
`torsion75`	`37.2400`	`-0.41819940`

CONOPT: infeasible: Back to top

Modelname	Time (CONOPT)	Status (CONOPT)
`arki0008`	`--`	`mstat( 5) sstat( 1)`
`glider100`	`--`	`mstat( 5) sstat( 1)`
`glider200`	`--`	`mstat( 5) sstat( 1)`

CONOPT: unbounded: Back to top

Modelname	Time (CONOPT)	Status (CONOPT)
`ex8_2_2`	`3.4400`	`mstat( 3) sstat( 1)`

CONOPT: fail: Back to top

Modelname	Time (CONOPT)	Status (CONOPT)
`arki0013`	`--`	`mstat( 6) sstat( 4)`
`arki0014`	`--`	`mstat( 6) sstat( 4)`
`rocket400`	`--`	`mstat( 6) sstat( 4)`

IPOPTMUMPS: all -- CONOPT: all : Back to top

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

A model is counted as solved if a feasible point has been found.

For time and timeratios, a shifted geometric mean is used, where unsolved instances are counted with twice the reslim (3600.00 seconds). The shift is 10s for time and 0.0001 for timeratios.

Modelname	Time (IPOPTMUMPS)	Time (CONOPT)	Ratio (IPOPTMUMPS/CONOPT)	Obj (IPOPTMUMPS)	Obj (CONOPT)
`arki0002`	`0.5000`	`1.4000`	`0.357`	`1.87252774`	`1.09905910`
`arki0003`	`110.0500`	`12.1100`	`9.088`	`3795.20606793`	`3795.20606459`
`arki0004`	`5.8300`	`1.3800`	`4.225`	`327.73301341`	`323.46703883`
`arki0008`	`133.3600`	`26.0900`	---	`mstat( 6) sstat( 4)`	`mstat( 5) sstat( 1)`
`arki0011`	`105.3900`	`7.8000`	`13.512`	`-224086.45997466`	`-224086.46003881`
`arki0012`	`172.9100`	`1016.2100`	`0.170`	`-224252.44185188`	`-224252.44569385`
`arki0013`	`148.0000`	`19.8300`	---	`-224253.08813525`	`mstat( 6) sstat( 4)`
`arki0014`	`109.5500`	`25.4900`	---	`-223976.86141185`	`mstat( 6) sstat( 4)`
`arki0015`	`9.0400`	`1.0600`	`8.528`	`-266.94068809`	`-271.73572350`
`arki0016`	`4.4500`	`843.3200`	`0.005`	`867.97316601`	`867.97316601`
`arki0017`	`3.5100`	`99.6400`	`0.035`	`-121.83308010`	`-121.83308010`
`arki0018`	`1.2200`	`1.5400`	`0.792`	`0.01045662`	`0.01045662`
`arki0020`	`0.5100`	`3.2100`	`0.159`	`-41.07495436`	`-41.07495436`
`arki0021`	`2.1100`	`81.8800`	`0.026`	`-72.58210091`	`-72.58210091`
`arki0022`	`5.2600`	`73.4400`	`0.072`	`-87.09909127`	`-87.09909127`
`arki0023`	`13.6100`	`14.2000`	`0.958`	`-153.66007775`	`-153.66007775`
`camshape400`	`0.9200`	`0.0800`	`11.500`	`-4.27568847`	`-4.27568848`
`camshape800`	`1.6700`	`0.3200`	`5.219`	`-4.27427413`	`-4.27427414`
`catmix100`	`0.1600`	`0.0800`	`2.000`	`-0.04806941`	`-0.04806939`
`catmix200`	`0.1800`	`0.0900`	`2.000`	`-0.04805914`	`-0.04805914`
`catmix400`	`0.4900`	`0.2300`	`2.130`	`-0.04805654`	`-0.04805654`
`catmix800`	`0.8000`	`0.7300`	`1.096`	`-0.04805590`	`-0.04805590`
`chain400`	`0.1500`	`0.2000`	`0.750`	`5.06862169`	`5.06862169`
`elec200`	`1473.1900`	`29.0300`	`50.747`	`18439.26774952`	`18438.99952062`
`ex8_2_2`	`3630.9100`	`3.4400`	---	`mstat( 6) sstat( 3)`	`mstat( 3) sstat( 1)`
`ex8_2_2a`	`8.3800`	`8.7700`	`0.956`	`-552.66625860`	`-552.66625940`
`ex8_2_2b`	`12.9500`	`7.7900`	`1.662`	`-552.66625954`	`-552.66625902`
`ex8_2_3a`	`17.8100`	`17.7600`	`1.003`	`-3731.07929639`	`-3731.07929542`
`ex8_2_3b`	`20.0300`	`16.0800`	`1.246`	`-3731.07929656`	`-3731.07929509`
`ex8_2_5a`	`7.8200`	`4.4100`	`1.773`	`-830.33806724`	`-830.33806698`
`ex8_2_5b`	`15.4100`	`3.2100`	`4.801`	`-830.33806724`	`-830.33806699`
`flowchan100`	`0.2600`	`0.0600`	`4.333`	`0.00000000`	`0.00000000`
`flowchan200`	`0.4200`	`0.1300`	`3.231`	`0.00000000`	`0.00000000`
`flowchan400`	`0.7200`	`0.7000`	`1.029`	`0.00000000`	`0.00000000`
`gasoil100`	`1.0100`	`0.3400`	`2.971`	`0.00523659`	`0.00523659`
`gasoil200`	`1.1600`	`0.5000`	`2.320`	`0.00523660`	`0.00523660`
`gasoil400`	`2.7300`	`1.5000`	`1.820`	`0.00523660`	`0.00523660`
`gasoil50`	`0.3900`	`0.1700`	`2.294`	`0.00523664`	`0.00523664`
`glider100`	`8.7200`	`3.8900`	---	`-250.00000000`	`mstat( 5) sstat( 1)`
`glider200`	`13.4600`	`11.3900`	---	`mstat( 5) sstat( 1)`	`mstat( 5) sstat( 1)`
`glider400`	`43.4900`	`528.6400`	`0.082`	`-250.00000000`	`-1247.97431754`
`glider50`	`1.4800`	`12.2400`	---	`mstat( 5) sstat( 1)`	`-1286.97737315`
`infeas1 (max)`	`1.1000`	`0.3600`	`3.056`	`13685.59646092`	`13685.59646095`
`jbearing100`	`9.1900`	`76.1000`	`0.121`	`-0.15504194`	`-0.15504196`
`jbearing25`	`1.1300`	`2.3700`	`0.477`	`-0.15401551`	`-0.15401554`
`jbearing50`	`2.3800`	`14.0100`	`0.170`	`-0.15482381`	`-0.15482422`
`jbearing75`	`5.5400`	`36.2300`	`0.153`	`-0.15498446`	`-0.15498453`
`lnts100`	`0.1900`	`0.1900`	`1.000`	`0.55459540`	`0.55459540`
`lnts200`	`0.2700`	`0.7400`	`0.365`	`0.55457702`	`0.55457702`
`lnts400`	`0.4500`	`1.9100`	`0.236`	`0.55457241`	`0.55457241`
`methanol100`	`1.2000`	`0.3200`	`3.750`	`0.00902229`	`0.00902229`
`methanol200`	`7.5900`	`0.6600`	`11.500`	`0.00902229`	`0.00902229`
`methanol400`	`10.3000`	`1.4800`	`6.959`	`0.00902229`	`0.00902229`
`methanol50`	`0.2900`	`0.1600`	`1.812`	`0.00902229`	`0.00902229`
`minsurf100`	`11.5400`	`78.2400`	`0.147`	`2.50694962`	`2.50694926`
`minsurf25`	`1.2400`	`1.3700`	`0.905`	`2.51948798`	`2.51948768`
`minsurf50`	`3.4100`	`12.0200`	`0.284`	`2.51489003`	`2.51488916`
`minsurf75`	`19.0600`	`37.2700`	`0.511`	`2.50568704`	`2.50568648`
`pinene100`	`1.0300`	`0.4400`	`2.341`	`19.87217015`	`19.87217015`
`pinene200`	`2.0900`	`1.4400`	`1.451`	`19.87216684`	`19.87216684`
`pinene25`	`0.5800`	`0.2800`	`2.071`	`19.87216552`	`19.87216552`
`pinene50`	`0.3800`	`0.2700`	`1.407`	`19.87216552`	`19.87216552`
`polygon100`	`7.7700`	`9.9600`	`0.780`	`-0.78505614`	`-0.78489329`
`polygon25`	`0.1400`	`0.3100`	`0.452`	`-0.77974054`	`-0.77914600`
`polygon50`	`2.1100`	`0.8800`	`2.398`	`-0.78213256`	`-0.78281345`
`polygon75`	`7.3300`	`4.5700`	`1.604`	`-0.78446376`	`-0.78367803`
`popdynm100`	`0.9100`	`5.0100`	`0.182`	`19746.52860217`	`19746.52860217`
`popdynm200`	`3.6300`	`10.3700`	`0.350`	`19746.52964660`	`19746.52964660`
`popdynm25`	`0.4900`	`0.7800`	`0.628`	`19752.21541511`	`19752.21541511`
`popdynm50`	`0.7600`	`2.1400`	`0.355`	`19746.54515628`	`19746.54515628`
`robot100`	`3600.0400`	`0.2800`	`12857.286`	`-2.2709461441873E+16`	`9.14268538`
`robot200`	`1.1600`	`1.1400`	`1.018`	`9.14139688`	`9.14139550`
`robot400`	`3.0100`	`2.8300`	`1.064`	`9.14102607`	`9.14102603`
`robot50`	`3600.0100`	`0.1700`	---	`mstat( 6) sstat( 3)`	`9.14687850`
`rocket100`	`0.7000`	`0.9500`	`0.737`	`-1.01283201`	`-1.01283202`
`rocket200`	`2.4100`	`4.1900`	`0.575`	`-1.01283568`	`-1.01283569`
`rocket400`	`3.0800`	`4.1800`	---	`-1.01283661`	`mstat( 6) sstat( 4)`
`torsion100`	`17.3900`	`68.0400`	`0.256`	`-0.41823920`	`-0.41823921`
`torsion25`	`1.2200`	`1.4700`	`0.830`	`-0.41751073`	`-0.41751073`
`torsion50`	`6.9400`	`10.1500`	`0.684`	`-0.41808762`	`-0.41808763`
`torsion75`	`10.1800`	`37.2400`	`0.273`	`-0.41819939`	`-0.41819940`

mean	16.69	21.70	---	---	---
unsolved	6.17%	8.64%