Solver Square Comparison

Solver Square Comparison: Considers all models.

Results created on 11/09/09 18:57:36 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 COINIPOPTDmumps 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:	COINIPOPTD-2.trc
Solvers used :	COINIPOPTDma27
	COINIPOPTDmumps
Modeltype(s)	`NLP`

	COINIPOPTDmumps: optimal	COINIPOPTDmumps: locally optimal	COINIPOPTDmumps: feasible	COINIPOPTDmumps: infeasible	COINIPOPTDmumps: unbounded	COINIPOPTDmumps: fail	COINIPOPTDmumps: 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 COINIPOPTDmumps	`13`	`60`	`1`	`3`	`-`	`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 -- COINIPOPTDmumps: optimal

Modelname	Time (COINIPOPTDma27)	Time (COINIPOPTDmumps)	Ratio (COINIPOPTDma27/COINIPOPTDmumps)	Obj (COINIPOPTDma27)	Obj (COINIPOPTDmumps)
`arki0018`	`0.2970`	`1.1790`	`0.252`	`0.01045662`	`0.01045662`
`arki0020`	`0.0580`	`0.1410`	`0.411`	`-41.07495436`	`-41.07495436`
`arki0021`	`0.1720`	`0.4440`	`0.387`	`-72.58210091`	`-72.58210091`
`arki0022`	`0.2960`	`0.6890`	`0.430`	`-87.09909127`	`-87.09909127`
`arki0023`	`0.5750`	`1.4030`	`0.410`	`-153.66007775`	`-153.66007775`
`jbearing100`	`0.4000`	`0.6650`	`0.602`	`-0.15504194`	`-0.15504194`
`jbearing25`	`0.1070`	`0.1570`	`0.682`	`-0.15401551`	`-0.15401551`
`jbearing50`	`0.2010`	`0.3140`	`0.640`	`-0.15482381`	`-0.15482381`
`jbearing75`	`0.2780`	`0.4640`	`0.599`	`-0.15498446`	`-0.15498446`
`minsurf100`	`0.5260`	`0.6810`	`0.772`	`2.50694962`	`2.50694962`
`minsurf25`	`0.1450`	`0.1500`	`0.967`	`2.51948798`	`2.51948798`
`minsurf50`	`0.2360`	`0.3140`	`0.752`	`2.51489003`	`2.51489003`
`minsurf75`	`1.3620`	`2.1080`	`0.646`	`2.50568661`	`2.50568721`

COINIPOPTDma27: locally optimal -- COINIPOPTDmumps: locally optimal

Modelname	Time (COINIPOPTDma27)	Time (COINIPOPTDmumps)	Ratio (COINIPOPTDma27/COINIPOPTDmumps)	Obj (COINIPOPTDma27)	Obj (COINIPOPTDmumps)
`arki0002`	`0.5130`	`0.3200`	`1.603`	`1.87252774`	`1.87252774`
`arki0004`	`2.4100`	`3.5800`	`0.673`	`323.46703883`	`327.73301341`
`arki0011`	`73.2350`	`91.9100`	`0.797`	`-224086.46003464`	`-224086.45997864`
`arki0012`	`56.1550`	`89.9340`	`0.624`	`-224252.42629882`	`-224252.27283280`
`arki0013`	`60.8560`	`154.5390`	`0.394`	`-224253.08745620`	`-224253.08721105`
`arki0014`	`50.4280`	`135.2720`	`0.373`	`-223977.03530617`	`-223977.06909780`
`arki0015`	`2.6520`	`5.7990`	`0.457`	`-266.94068809`	`-266.94068809`
`arki0016`	`11.9170`	`15.8850`	`0.750`	`867.97316601`	`867.97316601`
`arki0017`	`0.4020`	`1.4140`	`0.284`	`-121.83308011`	`-121.83308011`
`camshape400`	`0.1590`	`1.2920`	`0.123`	`-4.27569663`	`-4.27569663`
`camshape800`	`0.3430`	`150.9280`	`0.002`	`-4.27430687`	`-4.27430687`
`catmix100`	`0.0390`	`0.0990`	`0.394`	`-0.04806941`	`-0.04806941`
`catmix200`	`0.0450`	`0.0840`	`0.536`	`-0.04805914`	`-0.04805914`
`catmix400`	`0.0840`	`0.1540`	`0.545`	`-0.04805654`	`-0.04805654`
`catmix800`	`0.1620`	`0.2660`	`0.609`	`-0.04805590`	`-0.04805590`
`chain400`	`0.0160`	`0.0600`	`0.267`	`5.06862169`	`5.06862169`
`elec200`	`58.4470`	`51.8720`	`1.127`	`18439.26774952`	`18439.26774952`
`ex8_2_2a`	`2.5940`	`4.9920`	`0.520`	`-552.66625903`	`-552.66625903`
`ex8_2_2b`	`3.0450`	`6.8980`	`0.441`	`-552.66625998`	`-552.66625998`
`ex8_2_3a`	`7.1170`	`11.9870`	`0.594`	`-3731.07929678`	`-3731.07929678`
`ex8_2_3b`	`8.1910`	`13.8100`	`0.593`	`-3731.07929695`	`-3731.07929695`
`ex8_2_5a`	`2.3930`	`3.5250`	`0.679`	`-830.33806763`	`-830.33806763`
`ex8_2_5b`	`8.7250`	`10.1360`	`0.861`	`-830.33806763`	`-830.33806763`
`flowchan100`	`0.0450`	`0.1060`	`0.425`	`0.00000000`	`0.00000000`
`flowchan200`	`0.0910`	`0.2220`	`0.410`	`0.00000000`	`0.00000000`
`flowchan400`	`0.4490`	`0.8130`	`0.552`	`0.00000000`	`0.00000000`
`gasoil100`	`0.2030`	`0.4830`	`0.420`	`0.00523659`	`0.00523659`
`gasoil200`	`0.3470`	`0.7570`	`0.458`	`0.00523660`	`0.00523660`
`gasoil400`	`0.9890`	`1.7710`	`0.558`	`0.00523660`	`0.00523660`
`gasoil50`	`0.1190`	`0.1680`	`0.708`	`0.00523664`	`0.00523664`
`infeas1`	`0.3760`	`0.7690`	`0.489`	`13685.59647017`	`13685.59647017`
`lnts100`	`0.0280`	`0.3370`	`0.083`	`0.55459540`	`0.55459540`
`lnts200`	`0.0430`	`0.1380`	`0.312`	`0.55457702`	`0.55457702`
`lnts400`	`0.0830`	`0.2820`	`0.294`	`0.55457241`	`0.55457241`
`methanol100`	`0.2520`	`0.5090`	`0.495`	`0.00902229`	`0.00902229`
`methanol200`	`2.2430`	`5.2700`	`0.426`	`0.00902229`	`0.00902229`
`methanol400`	`4.5550`	`6.7100`	`0.679`	`0.00902229`	`0.00902229`
`methanol50`	`0.0810`	`0.1730`	`0.468`	`0.00902229`	`0.00902229`
`pinene100`	`0.1680`	`0.4800`	`0.350`	`19.87217015`	`19.87217015`
`pinene200`	`0.4250`	`1.0070`	`0.422`	`19.87216684`	`19.87216684`
`pinene25`	`0.0810`	`0.2610`	`0.310`	`19.87216552`	`19.87216552`
`pinene50`	`0.0810`	`0.2640`	`0.307`	`19.87216552`	`19.87216552`
`polygon100`	`3.7980`	`4.7510`	`0.799`	`-0.78505614`	`-0.78505614`
`polygon25`	`0.0350`	`0.1110`	`0.315`	`-0.77974054`	`-0.77974054`
`polygon50`	`0.6580`	`1.6330`	`0.403`	`-0.78213256`	`-0.78213256`
`polygon75`	`2.8940`	`6.1170`	`0.473`	`-0.78446376`	`-0.78446376`
`popdynm100`	`0.2590`	`0.5360`	`0.483`	`19746.52860214`	`19746.52860214`
`popdynm200`	`0.6550`	`1.3650`	`0.480`	`19746.52964658`	`19746.52964658`
`popdynm25`	`0.0990`	`0.2850`	`0.347`	`19752.21541508`	`19752.21541508`
`popdynm50`	`0.1490`	`0.8030`	`0.186`	`19746.54515625`	`19746.54515625`
`robot200`	`0.2740`	`0.8570`	`0.320`	`9.14139686`	`9.14139688`
`robot400`	`0.7520`	`2.6250`	`0.286`	`9.14102607`	`9.14102607`
`rocket100`	`1.8710`	`5.2810`	`0.354`	`-1.01283202`	`-1.01283202`
`rocket200`	`12.0200`	`31.9930`	`0.376`	`-1.01283569`	`-1.01283569`
`rocket400`	`118.6340`	`233.8110`	`0.507`	`-1.01283661`	`-1.01283661`
`torsion100`	`0.5540`	`0.7270`	`0.762`	`-0.41823920`	`-0.41823920`
`torsion25`	`0.1320`	`0.1620`	`0.815`	`-0.41751073`	`-0.41751073`
`torsion50`	`0.2660`	`0.3560`	`0.747`	`-0.41808762`	`-0.41808762`
`torsion75`	`0.4090`	`0.5350`	`0.764`	`-0.41819939`	`-0.41819939`

COINIPOPTDma27: locally optimal -- COINIPOPTDmumps: fail

Modelname	Time (COINIPOPTDma27)	Time (COINIPOPTDmumps)	Ratio (COINIPOPTDma27/COINIPOPTDmumps)	Obj (COINIPOPTDma27)	Status (COINIPOPTDmumps)
`arki0003`	`1499.9250`	`3622.7920`	---	`3795.19682438`	`mstat( 6)sstat( 3)`

COINIPOPTDma27: infeasible -- COINIPOPTDmumps: infeasible

Modelname	Time (COINIPOPTDma27)	Time (COINIPOPTDmumps)	Ratio (COINIPOPTDma27/COINIPOPTDmumps)	Status (COINIPOPTDma27)	Status (COINIPOPTDmumps)
`glider100`	`1.4750`	`2.1410`	---	`mstat( 5)sstat( 1)`	`mstat( 5)sstat( 1)`
`glider400`	`161.1040`	`7.9980`	---	`mstat( 5)sstat( 1)`	`mstat( 5)sstat( 1)`
`glider50`	`0.2920`	`0.8090`	---	`mstat( 5)sstat( 1)`	`mstat( 5)sstat( 1)`

COINIPOPTDma27: unbounded -- COINIPOPTDmumps: fail

Modelname	Time (COINIPOPTDma27)	Time (COINIPOPTDmumps)	Ratio (COINIPOPTDma27/COINIPOPTDmumps)	Status (COINIPOPTDma27)	Status (COINIPOPTDmumps)
`robot100`	`6.4560`	`3638.1290`	---	`mstat( 3)sstat( 1)`	`mstat( 6)sstat( 3)`

COINIPOPTDma27: fail -- COINIPOPTDmumps: locally optimal

Modelname	Time (COINIPOPTDma27)	Time (COINIPOPTDmumps)	Ratio (COINIPOPTDma27/COINIPOPTDmumps)	Status (COINIPOPTDma27)	Obj (COINIPOPTDmumps)
`glider200`	`3619.9990`	`1821.6560`	---	`mstat( 6)sstat( 3)`	`-1248.89636213`

COINIPOPTDma27: fail -- COINIPOPTDmumps: feasible

Modelname	Time (COINIPOPTDma27)	Time (COINIPOPTDmumps)	Ratio (COINIPOPTDma27/COINIPOPTDmumps)	Status (COINIPOPTDma27)	Obj (COINIPOPTDmumps)
`robot50`	`102.4360`	`41.6870`	---	`mstat( 6)sstat( 4)`	`-1.5576010946900E+16`

COINIPOPTDma27: fail -- COINIPOPTDmumps: fail

Modelname	Time (COINIPOPTDma27)	Time (COINIPOPTDmumps)	Ratio (COINIPOPTDma27/COINIPOPTDmumps)	Status (COINIPOPTDma27)	Status (COINIPOPTDmumps)
`arki0008`	`3627.7850`	`740.6630`	---	`mstat( 6)sstat( 3)`	`mstat( 6)sstat( 4)`
`ex8_2_2`	`3634.5650`	`NA`	---	`mstat( 6)sstat( 3)`	`mstat(13)sstat(13)`

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)`

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)`

COINIPOPTDma27: all -- COINIPOPTDmumps: all

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

Modelname	Time (COINIPOPTDma27)	Time (COINIPOPTDmumps)	Ratio (COINIPOPTDma27/ COINIPOPTDmumps)	Obj (COINIPOPTDma27)	Obj (COINIPOPTDmumps)
`arki0002`	`0.5130`	`0.3200`	`1.603`	`1.87252774`	`1.87252774`
`arki0003`	`1499.9250`	`3622.7920`	---	`3795.19682438`	`mstat( 6) sstat(3)`
`arki0004`	`2.4100`	`3.5800`	`0.673`	`323.46703883`	`327.73301341`
`arki0008`	`3627.7850`	`740.6630`	---	`mstat( 6) sstat(3)`	`mstat( 6) sstat(4)`
`arki0011`	`73.2350`	`91.9100`	`0.797`	`-224086.46003464`	`-224086.45997864`
`arki0012`	`56.1550`	`89.9340`	`0.624`	`-224252.42629882`	`-224252.27283280`
`arki0013`	`60.8560`	`154.5390`	`0.394`	`-224253.08745620`	`-224253.08721105`
`arki0014`	`50.4280`	`135.2720`	`0.373`	`-223977.03530617`	`-223977.06909780`
`arki0015`	`2.6520`	`5.7990`	`0.457`	`-266.94068809`	`-266.94068809`
`arki0016`	`11.9170`	`15.8850`	`0.750`	`867.97316601`	`867.97316601`
`arki0017`	`0.4020`	`1.4140`	`0.284`	`-121.83308011`	`-121.83308011`
`arki0018`	`0.2970`	`1.1790`	`0.252`	`0.01045662`	`0.01045662`
`arki0020`	`0.0580`	`0.1410`	`0.411`	`-41.07495436`	`-41.07495436`
`arki0021`	`0.1720`	`0.4440`	`0.387`	`-72.58210091`	`-72.58210091`
`arki0022`	`0.2960`	`0.6890`	`0.430`	`-87.09909127`	`-87.09909127`
`arki0023`	`0.5750`	`1.4030`	`0.410`	`-153.66007775`	`-153.66007775`
`camshape400`	`0.1590`	`1.2920`	`0.123`	`-4.27569663`	`-4.27569663`
`camshape800`	`0.3430`	`150.9280`	`0.002`	`-4.27430687`	`-4.27430687`
`catmix100`	`0.0390`	`0.0990`	`0.394`	`-0.04806941`	`-0.04806941`
`catmix200`	`0.0450`	`0.0840`	`0.536`	`-0.04805914`	`-0.04805914`
`catmix400`	`0.0840`	`0.1540`	`0.545`	`-0.04805654`	`-0.04805654`
`catmix800`	`0.1620`	`0.2660`	`0.609`	`-0.04805590`	`-0.04805590`
`chain400`	`0.0160`	`0.0600`	`0.267`	`5.06862169`	`5.06862169`
`elec200`	`58.4470`	`51.8720`	`1.127`	`18439.26774952`	`18439.26774952`
`ex8_2_2`	`3634.5650`	`NA`	---	`mstat( 6) sstat(3)`	`mstat(13) sstat(13)`
`ex8_2_2a`	`2.5940`	`4.9920`	`0.520`	`-552.66625903`	`-552.66625903`
`ex8_2_2b`	`3.0450`	`6.8980`	`0.441`	`-552.66625998`	`-552.66625998`
`ex8_2_3a`	`7.1170`	`11.9870`	`0.594`	`-3731.07929678`	`-3731.07929678`
`ex8_2_3b`	`8.1910`	`13.8100`	`0.593`	`-3731.07929695`	`-3731.07929695`
`ex8_2_5a`	`2.3930`	`3.5250`	`0.679`	`-830.33806763`	`-830.33806763`
`ex8_2_5b`	`8.7250`	`10.1360`	`0.861`	`-830.33806763`	`-830.33806763`
`flowchan100`	`0.0450`	`0.1060`	`0.425`	`0.00000000`	`0.00000000`
`flowchan200`	`0.0910`	`0.2220`	`0.410`	`0.00000000`	`0.00000000`
`flowchan400`	`0.4490`	`0.8130`	`0.552`	`0.00000000`	`0.00000000`
`gasoil100`	`0.2030`	`0.4830`	`0.420`	`0.00523659`	`0.00523659`
`gasoil200`	`0.3470`	`0.7570`	`0.458`	`0.00523660`	`0.00523660`
`gasoil400`	`0.9890`	`1.7710`	`0.558`	`0.00523660`	`0.00523660`
`gasoil50`	`0.1190`	`0.1680`	`0.708`	`0.00523664`	`0.00523664`
`glider100`	`1.4750`	`2.1410`	---	`mstat( 5) sstat(1)`	`mstat( 5) sstat(1)`
`glider200`	`3619.9990`	`1821.6560`	---	`mstat( 6) sstat(3)`	`-1248.89636213`
`glider400`	`161.1040`	`7.9980`	---	`mstat( 5) sstat(1)`	`mstat( 5) sstat(1)`
`glider50`	`0.2920`	`0.8090`	---	`mstat( 5) sstat(1)`	`mstat( 5) sstat(1)`
`infeas1 (max)`	`0.3760`	`0.7690`	`0.489`	`13685.59647017`	`13685.59647017`
`jbearing100`	`0.4000`	`0.6650`	`0.602`	`-0.15504194`	`-0.15504194`
`jbearing25`	`0.1070`	`0.1570`	`0.682`	`-0.15401551`	`-0.15401551`
`jbearing50`	`0.2010`	`0.3140`	`0.640`	`-0.15482381`	`-0.15482381`
`jbearing75`	`0.2780`	`0.4640`	`0.599`	`-0.15498446`	`-0.15498446`
`lnts100`	`0.0280`	`0.3370`	`0.083`	`0.55459540`	`0.55459540`
`lnts200`	`0.0430`	`0.1380`	`0.312`	`0.55457702`	`0.55457702`
`lnts400`	`0.0830`	`0.2820`	`0.294`	`0.55457241`	`0.55457241`
`methanol100`	`0.2520`	`0.5090`	`0.495`	`0.00902229`	`0.00902229`
`methanol200`	`2.2430`	`5.2700`	`0.426`	`0.00902229`	`0.00902229`
`methanol400`	`4.5550`	`6.7100`	`0.679`	`0.00902229`	`0.00902229`
`methanol50`	`0.0810`	`0.1730`	`0.468`	`0.00902229`	`0.00902229`
`minsurf100`	`0.5260`	`0.6810`	`0.772`	`2.50694962`	`2.50694962`
`minsurf25`	`0.1450`	`0.1500`	`0.967`	`2.51948798`	`2.51948798`
`minsurf50`	`0.2360`	`0.3140`	`0.752`	`2.51489003`	`2.51489003`
`minsurf75`	`1.3620`	`2.1080`	`0.646`	`2.50568661`	`2.50568721`
`pinene100`	`0.1680`	`0.4800`	`0.350`	`19.87217015`	`19.87217015`
`pinene200`	`0.4250`	`1.0070`	`0.422`	`19.87216684`	`19.87216684`
`pinene25`	`0.0810`	`0.2610`	`0.310`	`19.87216552`	`19.87216552`
`pinene50`	`0.0810`	`0.2640`	`0.307`	`19.87216552`	`19.87216552`
`polygon100`	`3.7980`	`4.7510`	`0.799`	`-0.78505614`	`-0.78505614`
`polygon25`	`0.0350`	`0.1110`	`0.315`	`-0.77974054`	`-0.77974054`
`polygon50`	`0.6580`	`1.6330`	`0.403`	`-0.78213256`	`-0.78213256`
`polygon75`	`2.8940`	`6.1170`	`0.473`	`-0.78446376`	`-0.78446376`
`popdynm100`	`0.2590`	`0.5360`	`0.483`	`19746.52860214`	`19746.52860214`
`popdynm200`	`0.6550`	`1.3650`	`0.480`	`19746.52964658`	`19746.52964658`
`popdynm25`	`0.0990`	`0.2850`	`0.347`	`19752.21541508`	`19752.21541508`
`popdynm50`	`0.1490`	`0.8030`	`0.186`	`19746.54515625`	`19746.54515625`
`robot100`	`6.4560`	`3638.1290`	---	`mstat( 3) sstat(1)`	`mstat( 6) sstat(3)`
`robot200`	`0.2740`	`0.8570`	`0.320`	`9.14139686`	`9.14139688`
`robot400`	`0.7520`	`2.6250`	`0.286`	`9.14102607`	`9.14102607`
`robot50`	`102.4360`	`41.6870`	---	`mstat( 6) sstat(4)`	`-1.5576010946900E+16`
`rocket100`	`1.8710`	`5.2810`	`0.354`	`-1.01283202`	`-1.01283202`
`rocket200`	`12.0200`	`31.9930`	`0.376`	`-1.01283569`	`-1.01283569`
`rocket400`	`118.6340`	`233.8110`	`0.507`	`-1.01283661`	`-1.01283661`
`torsion100`	`0.5540`	`0.7270`	`0.762`	`-0.41823920`	`-0.41823920`
`torsion25`	`0.1320`	`0.1620`	`0.815`	`-0.41751073`	`-0.41751073`
`torsion50`	`0.2660`	`0.3560`	`0.747`	`-0.41808762`	`-0.41808762`
`torsion75`	`0.4090`	`0.5350`	`0.764`	`-0.41819939`	`-0.41819939`