Resource Time Comparison - Optimal/Feasible Solved Models

Table A: Considers only models solved optimal/feasible by both solvers.

Date / Time: 11/15/02 12:53:26

Total resource time for models solved optimal/feasible by solver A and solver B.

See the solver return definitions for optimal/feasible model and solve statuses. Solutions are not checked for how close they are to oneanother. Resource times are considered the same, if they are within 10% of eachother. A solver is considered faster than another, if it is less than 50% faster than the other. A solver is considered much faster than another, if it is more than 50% faster than the other.

A solver is considered to have a better objective function value, if the relative objective value difference is greater than 1.00E-06.

Tracefile 1 :	`SNOPT.TXT`
Tracefile 2 :	`OQMSCONOPT.TXT`
Solvers used :	`SNOPT`
	`OQNLP/CONOPT`
Modeltype(s)	NLP

	Total	Obj. SNOPT better	Obj. same	Obj. OQNLP/CONOPTbetter
Solver SNOPT much faster :	`13`	-	`9`	`4`
Solver SNOPT faster :	-	-	-	-
Solvers perform the same:	-	-	-	-
Solver OQNLP/CONOPT faster :	`9`	-	`9`	-
Solver OQNLP/CONOPT much faster :	`67`	-	`52`	`15`
Total models solved optimal/feasible :	`89`	-	`70`	`19`

Solver return definition:

Outcome	Model Status	Solver Status
optimal	1 or 15	1
feasible	2 or 16 or 17	1 or 2 or 3 or 4 or 5

Resource Times:

Resource times (as in trace file) listed in seconds.

Models for each resource time category. Listed are the solver resource times in seconds, as well as the ratio of resource times for the two solvers if both solved optimal/feasible.
Also listed are the objective values 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-06.
Solver resource time ratios for a particular model are listed only if both solvers are optimal/feasible and if one solver has resource time greater than 5.00E-02.

Solver

Modelname SNOPT OQNLP/CONOPT

EX14_1_1

EX14_1_3

EX6_2_5

EX7_2_3

EX8_1_7

EX8_3_6

EX8_4_3

EX8_4_8

EX9_2_6

Back align=right>Back to top SNOPT much faster - Obj same for both solvers: Ratio (SNOPT / OQNLP/CONOPT)Obj SNOPTObj OQNLP/CONOPT 0.20311.14100.178 0.00000000E+00 0.00000000E+00 0.08980.51600.174 0.00000000E+00 0.00000000E+00 0.14061.53100.092 -7.07520778E+01 -7.07520778E+01 0.05080.95300.053 7.04924625E+03 7.04924802E+03 0.06252.98500.021 2.93108307E-02 2.93108309E-02 0.53138.25000.064 -5.00000000E-01 -4.99999999E-01 0.38674.84400.080 4.64971568E-03 4.64971529E-03 0.093816.54700.006 3.32184733E+00 3.32184731E+00 0.07810.64100.122 -1.00000000E+00 -1.00000000E+00 to top

Solver SNOPT much faster - Obj of OQNLP/CONOPT better:

Modelname	SNOPT	OQNLP/CONOPT	Ratio (SNOPT / OQNLP/CONOPT)	Obj SNOPT	Obj OQNLP/CONOPT
`EX5_4_4`	`0.0508`	`6.0310`	`0.008`	`1.18416092E+04`	`1.00777754E+04`
`EX8_3_9`	`0.3281`	`15.5780`	`0.021`	`-7.59265470E-01`	`-7.63001934E-01`
`EX8_4_5`	`0.0625`	`1.3910`	`0.045`	`1.22529635E-03`	`3.07485745E-04`
`EX8_4_7`	`0.1563`	`8.6400`	`0.018`	`2.90473374E+01`	`2.90473067E+01`

Solver OQNLP/CONOPT faster - Obj same for both solvers:

Modelname	SNOPT	OQNLP/CONOPT	Ratio (SNOPT / OQNLP/CONOPT)	Obj SNOPT	Obj OQNLP/CONOPT
`EX14_1_5`	`0.0313`	`0.4840`	`0.065`	`0.00000000E+00`	`0.00000000E+00`
`EX14_1_9`	`0.0313`	`0.3280`	`0.095`	`0.00000000E+00`	`0.00000000E+00`
`EX14_2_2`	`0.0313`	`0.4530`	`0.069`	`0.00000000E+00`	`0.00000000E+00`
`EX14_2_5`	`0.0313`	`0.5310`	`0.059`	`0.00000000E+00`	`0.00000000E+00`
`EX14_2_8`	`0.0313`	`0.4530`	`0.069`	`0.00000000E+00`	`0.00000000E+00`
`EX14_2_9`	`0.0313`	`0.4690`	`0.067`	`0.00000000E+00`	`0.00000000E+00`
`EX4_1_8`	`0.0313`	`0.5150`	`0.061`	`-1.67388932E+01`	`-1.67388932E+01`
`EX7_2_1`	`3.5156`	`2.9210`	`1.204`	`1.22722603E+03`	`1.22722608E+03`
`EX7_3_2`	`0.0313`	`0.4690`	`0.067`	`1.08986390E+00`	`1.08986397E+00`

Solver OQNLP/CONOPT much faster - Obj same for both solvers:

Modelname	SNOPT	OQNLP/CONOPT	Ratio (SNOPT / OQNLP/CONOPT)	Obj SNOPT	Obj OQNLP/CONOPT
`EX14_1_2`	`0.0469`	`0.8430`	`0.056`	`0.00000000E+00`	`0.00000000E+00`
`EX14_2_1`	`0.0469`	`0.6880`	`0.068`	`0.00000000E+00`	`0.00000000E+00`
`EX14_2_3`	`0.0156`	`0.8430`	`0.019`	`0.00000000E+00`	`0.00000000E+00`
`EX14_2_4`	`0.0273`	`0.8280`	`0.033`	`0.00000000E+00`	`0.00000000E+00`
`EX14_2_6`	`0.0469`	`0.7500`	`0.063`	`0.00000000E+00`	`0.00000000E+00`
`EX14_2_7`	`0.0352`	`1.0310`	`0.034`	`0.00000000E+00`	`0.00000000E+00`
`EX2_1_1`	`0.0352`	`1.5000`	`0.023`	`-1.70000000E+01`	`-1.70000000E+01`
`EX2_1_2`	`0.0117`	`0.9850`	`0.012`	`-2.13000000E+02`	`-2.13000000E+02`
`EX2_1_3`	`0.0156`	`0.8280`	`0.019`	`-1.50000000E+01`	`-1.50000000E+01`
`EX2_1_4`	`0.0313`	`0.9060`	`0.034`	`-1.10000000E+01`	`-1.10000000E+01`
`EX2_1_5`	`0.0352`	`1.5000`	`0.023`	`-2.68014632E+02`	`-2.68014632E+02`
`EX2_1_6`	`0.0469`	`1.2810`	`0.037`	`-3.90000000E+01`	`-3.90000000E+01`
`EX2_1_7`	`0.0313`	`1.0620`	`0.029`	`-4.15041013E+03`	`-4.15041013E+03`
`EX2_1_9`	`0.0156`	`1.2500`	`0.013`	`-3.75000000E-01`	`-3.75000000E-01`
`EX3_1_1`	`0.0313`	`1.0620`	`0.029`	`7.04924801E+03`	`7.04924802E+03`
`EX3_1_2`	`0.0469`	`1.3280`	`0.035`	`-3.06655387E+04`	`-3.06655387E+04`
`EX3_1_3`	`0.0156`	`0.6090`	`0.026`	`-3.10000000E+02`	`-3.10000000E+02`
`EX3_1_4`	`0.0352`	`1.0310`	`0.034`	`-4.00000000E+00`	`-4.00000000E+00`
`EX4_1_2`	`0.0313`	`1.0000`	`0.031`	`-6.63500097E+02`	`-6.63500097E+02`
`EX4_1_3`	`0.0273`	`0.8900`	`0.031`	`-4.43671705E+02`	`-4.43671705E+02`
`EX4_1_4`	`0.0313`	`1.1100`	`0.028`	`0.00000000E+00`	`0.00000000E+00`
`EX4_1_5`	`0.0313`	`6.7350`	`0.005`	`0.00000000E+00`	`0.00000000E+00`
`EX4_1_6`	`0.0156`	`0.8440`	`0.019`	`7.00000000E+00`	`7.00000000E+00`
`EX4_1_7`	`0.0352`	`1.1560`	`0.030`	`-7.50000000E+00`	`-7.50000000E+00`
`EX4_1_9`	`0.0273`	`1.0620`	`0.026`	`-5.50801327E+00`	`-5.50801327E+00`
`EX5_2_2_CASE2`	`0.0313`	`1.8600`	`0.017`	`0.00000000E+00`	`0.00000000E+00`
`EX5_4_2`	`7.8438`	`0.6710`	`11.690`	`7.51223014E+03`	`7.51223014E+03`
`EX6_1_1`	`0.0313`	`0.8600`	`0.036`	`-2.01983116E-02`	`-2.01983120E-02`
`EX6_1_2`	`0.0352`	`1.6250`	`0.022`	`-3.24637501E-02`	`-3.24637501E-02`
`EX6_1_4`	`0.0352`	`0.7810`	`0.045`	`-2.94541288E-01`	`-2.94541288E-01`
`EX6_2_11`	`0.0313`	`0.6560`	`0.048`	`-2.67240776E-06`	`-2.67240938E-06`
`EX6_2_12`	`0.0469`	`0.8120`	`0.058`	`2.89194748E-01`	`2.89194748E-01`
`EX6_2_13`	`0.0156`	`2.4690`	`0.006`	`-2.16209437E-01`	`-2.16209437E-01`
`EX6_2_14`	`0.0273`	`1.1410`	`0.024`	`-6.95357935E-01`	`-6.95357935E-01`
`EX6_2_7`	`0.0469`	`1.1710`	`0.040`	`-1.60847615E-01`	`-1.60847616E-01`
`EX6_2_8`	`0.0352`	`1.1400`	`0.031`	`-2.70063488E-02`	`-2.70063488E-02`
`EX6_2_9`	`0.0313`	`1.0000`	`0.031`	`-3.40661841E-02`	`-3.40661844E-02`
`EX7_2_2`	`0.0313`	`2.6400`	`0.012`	`-3.88811438E-01`	`-3.88811434E-01`
`EX7_3_3`	`0.0156`	`2.6410`	`0.006`	`1.14477980E+00`	`1.14477980E+00`
`EX7_3_4`	`0.0313`	`0.9530`	`0.033`	`1.00000000E+01`	`1.00000000E+01`
`EX8_1_1`	`0.0313`	`1.2810`	`0.024`	`-2.02180678E+00`	`-2.02180678E+00`
`EX8_1_3`	`0.0313`	`1.3750`	`0.023`	`3.00000000E+01`	`3.00000000E+01`
`EX8_1_8`	`0.0352`	`2.5780`	`0.014`	`-3.88811438E-01`	`-3.88811434E-01`
`EX8_4_1`	`0.0313`	`2.0780`	`0.015`	`6.18572760E-01`	`6.18572759E-01`
`EX8_4_2`	`0.0469`	`3.4060`	`0.014`	`4.85152487E-01`	`4.85152486E-01`
`EX8_4_4`	`0.0313`	`1.5000`	`0.021`	`2.12459839E-01`	`2.12459839E-01`
`EX9_1_4`	`0.0313`	`1.4210`	`0.022`	`-3.70000000E+01`	`-3.70000000E+01`
`EX9_1_8`	`0.0273`	`1.1880`	`0.023`	`-3.25000000E+00`	`-3.25000000E+00`
`EX9_2_1`	`0.0313`	`3.2030`	`0.010`	`1.69999992E+01`	`1.70000000E+01`
`EX9_2_4`	`0.0313`	`2.1100`	`0.015`	`5.00000000E-01`	`5.00000000E-01`
`EX9_2_7`	`0.0273`	`3.2970`	`0.008`	`1.69999992E+01`	`1.70000000E+01`
`EX9_2_8`	`0.0156`	`0.6250`	`0.025`	`1.50000000E+00`	`1.50000000E+00`

Solver OQNLP/CONOPT much faster - Obj of OQNLP/CONOPT better:

Modelname	SNOPT	OQNLP/CONOPT	Ratio (SNOPT / OQNLP/CONOPT)	Obj SNOPT	Obj OQNLP/CONOPT
`EX14_1_6`	`0.0313`	`0.6250`	`0.050`	`1.00000000E+00`	`0.00000000E+00`
`EX14_1_7`	`0.0313`	`0.5940`	`0.053`	`7.04274947E+00`	`1.34990213E-01`
`EX14_1_8`	`0.0469`	`0.6880`	`0.068`	`4.14158858E-02`	`0.00000000E+00`
`EX2_1_10`	`0.0469`	`1.0630`	`0.044`	`1.33718845E+05`	`4.93180180E+04`
`EX2_1_8`	`0.0156`	`2.2180`	`0.007`	`2.52870000E+04`	`1.59900000E+04`
`EX4_1_1`	`0.0469`	`1.0150`	`0.046`	`-5.19978061E-01`	`-7.48731236E+00`
`EX5_2_2_CASE1`	`0.0273`	`0.7190`	`0.038`	`0.00000000E+00`	`-4.00000000E+02`
`EX5_2_2_CASE3`	`0.0273`	`0.6410`	`0.043`	`0.00000000E+00`	`-7.50000000E+02`
`EX5_2_4`	`0.0313`	`0.5780`	`0.054`	`-1.00000000E+02`	`-4.50000000E+02`
`EX5_2_5`	`0.0313`	`4.1410`	`0.008`	`-1.90000000E+03`	`-3.50000000E+03`
`EX7_2_4`	`0.0469`	`5.3590`	`0.009`	`4.20285303E+00`	`3.91801023E+00`
`EX7_3_5`	`0.0313`	`1.0310`	`0.030`	`1.20689655E+00`	`0.00000000E+00`
`EX8_1_2`	`0.0156`	`1.3600`	`0.011`	`2.80345848E+00`	`-1.07086102E+00`
`EX9_1_5`	`0.0313`	`0.5470`	`0.057`	`4.00000000E+00`	`-1.00000000E+00`
`EX9_2_3`	`0.0313`	`7.5470`	`0.004`	`5.00000000E+00`	`0.00000000E+00`