Solver Square Comparison

Solver Square Comparison: Considers all models.

Date / Time: 08/24/07 21:45:30

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 ALPHAECP is represented on the left (rows) and solver DICOPT 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 :	`2-AlphaECP-1.trc.convex`
Tracefile 2 :	`4-DICOPT-1.trc.convex`
Solvers used :	`ALPHAECP`
	`DICOPT`
Modeltype(s)	`MINLP`

	DICOPT: optimal	DICOPT: feasible	DICOPT: infeasible	DICOPT: unbounded	DICOPT: fail	DICOPT: no data	total ALPHAECP
ALPHAECP: optimal	-	-	-	-	-	-	`-`
ALPHAECP: feasible	-	`29`	-	-	`5`	-	`34`
ALPHAECP: infeasible	-	-	-	-	-	-	`-`
ALPHAECP: unbounded	-	-	-	-	-	-	`-`
ALPHAECP: fail	-	`1`	-	-	`3`	-	`4`
ALPHAECP: no data	-	-	-	-	-	-	`-`
total DICOPT	`-`	`30`	`-`	`-`	`8`	`-`	`38`

Solver return definitions:

Outcome	Model Status	Solver Status
optimal	1 or 15	1
locally optimal	2	any
feasible	8 or 16	1 or 2 or 3 or 4 or 5
infeasible	4 or 5 or 10 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.

ALPHAECP: feasible -- DICOPT: feasible Back to top

Modelname	Time (ALPHAECP)	Time (DICOPT)	Ratio (ALPHAECP/DICOPT)	Obj (ALPHAECP)	Obj (DICOPT)
`alan`	`1.0000`	`0.0200`	`50.000`	`2.92500000`	`3.00000000`
`batch`	`2.0000`	`0.0400`	`50.000`	`285506.48149069`	`285506.50824405`
`du-opt`	`1124.0000`	`0.1200`	`9366.667`	`3.55567908`	`108.84574029`
`du-opt5`	`453.0000`	`0.1100`	`4118.182`	`8.07307759`	`50.76141757`
`ex1223`	`3.0000`	`0.0300`	`100.000`	`4.57957678`	`4.57958240`
`ex1223a`	`3.0000`	`0.0300`	`100.000`	`4.57957997`	`4.57958240`
`ex1223b`	`3.0000`	`0.0500`	`60.000`	`4.57957678`	`4.57958240`
`fac1`	`83.0000`	`0.0400`	`2075.000`	`160912612.35016900`	`160912612.35016900`
`fac3`	`8.0000`	`0.1600`	`50.000`	`31982309.84800000`	`31982309.84800000`
`m3`	`2.0000`	`0.1000`	`20.000`	`37.80000000`	`37.80000000`
`m6`	`7.0000`	`2.3700`	`2.954`	`82.25687690`	`82.25687691`
`m7`	`33.0000`	`6.5300`	`5.054`	`106.75687690`	`180.35761902`
`meanvarx`	`1.0000`	`0.0400`	`25.000`	`14.36907510`	`14.36923211`
`nvs03`	`1.0000`	`0.0200`	`50.000`	`16.00000000`	`16.00000000`
`nvs10`	`2.0000`	`0.1100`	`18.182`	`-310.80000000`	`-310.80000000`
`risk2bpb`	`2.0000`	`0.2200`	`9.091`	`-55.87613940`	`-55.87613940`
`st_e14`	`2.0000`	`0.0500`	`40.000`	`4.57957678`	`4.57958240`
`st_miqp1`	`1.0000`	`0.0200`	`50.000`	`281.00000000`	`281.00000000`
`st_miqp2`	`1.0000`	`0.0200`	`50.000`	`2.00000000`	`5.00000000`
`stockcycle`	`3600.0000`	`0.2000`	`18000.000`	`436419.12998549`	`382333.83192308`
`st_test5`	`1.0000`	`0.0200`	`50.000`	`-110.00000000`	`-110.00000000`
`st_test6`	`1.0000`	`0.0400`	`25.000`	`471.00000000`	`471.00000000`
`st_test8`	`1.0000`	`0.0400`	`25.000`	`-29605.00000000`	`-29575.00000000`
`st_testgr1`	`2.0000`	`0.0400`	`50.000`	`-12.81160000`	`-9.57515000`
`st_testgr3`	`1.0000`	`0.0300`	`33.333`	`-20.59000000`	`-20.59000000`
`st_testph4`	`1.0000`	`0.0200`	`50.000`	`-80.50000000`	`-80.50000000`
`synthes1`	`1.0000`	`0.0300`	`33.333`	`6.00965002`	`6.00975891`
`synthes2`	`5.0000`	`0.0200`	`250.000`	`73.03454960`	`74.29448652`
`synthes3`	`4.0000`	`0.0700`	`57.143`	`68.00932736`	`76.41938054`

ALPHAECP: feasible -- DICOPT: fail Back to top

Modelname	Time (ALPHAECP)	Time (DICOPT)	Ratio (ALPHAECP/DICOPT)	Obj (ALPHAECP)	Status (DICOPT)
`fo7`	`504.0000`	`31.2300`	---	`20.72918438`	`mstat( 9) sstat( 4)`
`o7`	`3606.0000`	`151.4200`	---	`153.81988735`	`mstat( 9) sstat( 2)`
`st_e35`	`0.0000`	`0.0000`	---	`107419.80448037`	`mstat( 9) sstat( 1)`
`st_miqp3`	`1.0000`	`NA`	---	`-6.00000000`	`mstat(13) sstat(13)`
`st_miqp4`	`1.0000`	`NA`	---	`-4574.00000000`	`mstat(13) sstat(13)`

ALPHAECP: fail -- DICOPT: feasible Back to top

Modelname	Time (ALPHAECP)	Time (DICOPT)	Ratio (ALPHAECP/DICOPT)	Status (ALPHAECP)	Obj (DICOPT)
`risk2b`	`4.0000`	`0.1800`	---	`mstat(14) sstat(10)`	`-55.87613940`

ALPHAECP: fail -- DICOPT: fail Back to top

Modelname	Time (ALPHAECP)	Time (DICOPT)	Ratio (ALPHAECP/DICOPT)	Status (ALPHAECP)	Status (DICOPT)
`tls12`	`3601.0000`	`1182.4400`	---	`mstat(14) sstat( 3)`	`mstat( 9) sstat( 4)`
`tls6`	`3600.0000`	`83.7700`	---	`mstat(14) sstat( 3)`	`mstat( 9) sstat( 2)`
`tls7`	`3601.0000`	`86.1100`	---	`mstat(14) sstat( 3)`	`mstat( 9) sstat( 2)`

ALPHAECP: feasible: Back to top

Modelname	Time (ALPHAECP)	Obj (ALPHAECP)
`alan`	`1.0000`	`2.92500000`
`batch`	`2.0000`	`285506.48149069`
`du-opt`	`1124.0000`	`3.55567908`
`du-opt5`	`453.0000`	`8.07307759`
`ex1223`	`3.0000`	`4.57957678`
`ex1223a`	`3.0000`	`4.57957997`
`ex1223b`	`3.0000`	`4.57957678`
`fac1`	`83.0000`	`160912612.35016900`
`fac3`	`8.0000`	`31982309.84800000`
`fo7`	`504.0000`	`20.72918438`
`gbd`	`1.0000`	`2.20000000`
`m3`	`2.0000`	`37.80000000`
`m6`	`7.0000`	`82.25687690`
`m7`	`33.0000`	`106.75687690`
`meanvarx`	`1.0000`	`14.36907510`
`nvs03`	`1.0000`	`16.00000000`
`nvs10`	`2.0000`	`-310.80000000`
`o7`	`3606.0000`	`153.81988735`
`risk2bpb`	`2.0000`	`-55.87613940`
`st_e14`	`2.0000`	`4.57957678`
`st_e35`	`0.0000`	`107419.80448037`
`st_miqp1`	`1.0000`	`281.00000000`
`st_miqp2`	`1.0000`	`2.00000000`
`st_miqp3`	`1.0000`	`-6.00000000`
`st_miqp4`	`1.0000`	`-4574.00000000`
`st_miqp5`	`1.0000`	`-333.88903104`
`stockcycle`	`3600.0000`	`436419.12998549`
`st_test5`	`1.0000`	`-110.00000000`
`st_test6`	`1.0000`	`471.00000000`
`st_test8`	`1.0000`	`-29605.00000000`
`st_testgr1`	`2.0000`	`-12.81160000`
`st_testgr3`	`1.0000`	`-20.59000000`
`st_testph4`	`1.0000`	`-80.50000000`
`synthes1`	`1.0000`	`6.00965002`
`synthes2`	`5.0000`	`73.03454960`
`synthes3`	`4.0000`	`68.00932736`

ALPHAECP: fail: Back to top

Modelname	Time (ALPHAECP)	Status (ALPHAECP)
`risk2b`	`--`	`mstat(14) sstat(10)`
`tls12`	`--`	`mstat(14) sstat( 3)`
`tls6`	`--`	`mstat(14) sstat( 3)`
`tls7`	`--`	`mstat(14) sstat( 3)`

DICOPT: feasible: Back to top

Modelname	Time (DICOPT)	Obj (DICOPT)
`alan`	`0.0200`	`3.00000000`
`batch`	`0.0400`	`285506.50824405`
`du-opt`	`0.1200`	`108.84574029`
`du-opt5`	`0.1100`	`50.76141757`
`ex1223`	`0.0300`	`4.57958240`
`ex1223a`	`0.0300`	`4.57958240`
`ex1223b`	`0.0500`	`4.57958240`
`fac1`	`0.0400`	`160912612.35016900`
`fac3`	`0.1600`	`31982309.84800000`
`m3`	`0.1000`	`37.80000000`
`m6`	`2.3700`	`82.25687691`
`m7`	`6.5300`	`180.35761902`
`meanvarx`	`0.0400`	`14.36923211`
`nvs03`	`0.0200`	`16.00000000`
`nvs10`	`0.1100`	`-310.80000000`
`risk2b`	`0.1800`	`-55.87613940`
`risk2bpb`	`0.2200`	`-55.87613940`
`st_e14`	`0.0500`	`4.57958240`
`st_miqp1`	`0.0200`	`281.00000000`
`st_miqp2`	`0.0200`	`5.00000000`
`stockcycle`	`0.2000`	`382333.83192308`
`st_test5`	`0.0200`	`-110.00000000`
`st_test6`	`0.0400`	`471.00000000`
`st_test8`	`0.0400`	`-29575.00000000`
`st_testgr1`	`0.0400`	`-9.57515000`
`st_testgr3`	`0.0300`	`-20.59000000`
`st_testph4`	`0.0200`	`-80.50000000`
`synthes1`	`0.0300`	`6.00975891`
`synthes2`	`0.0200`	`74.29448652`
`synthes3`	`0.0700`	`76.41938054`

DICOPT: fail: Back to top

Modelname	Time (DICOPT)	Status (DICOPT)
`fo7`	`--`	`mstat( 9) sstat( 4)`
`o7`	`--`	`mstat( 9) sstat( 2)`
`st_e35`	`--`	`mstat( 9) sstat( 1)`
`st_miqp3`	`--`	`mstat(13) sstat(13)`
`st_miqp4`	`--`	`mstat(13) sstat(13)`
`tls12`	`--`	`mstat( 9) sstat( 4)`
`tls6`	`--`	`mstat( 9) sstat( 2)`
`tls7`	`--`	`mstat( 9) sstat( 2)`