Configuring the optimizer

BenchmarkingEconomicEfficiency.jl will use a default optimizer/solver for each DEA model, as shown in the next table.

Model	Function	Specific Options	Problem type	Default Optimizer
Profit Russell	`deaprofitrussell`		NLP	Ipopt
Profit Additive	`deaprofitadd`		LP	GLPK
Profit ERG=SBM	`deaprofiterg`		LP	GLPK
Profit DDF	`deaprofit`		LP	GLPK
Profit Hölder	`deaprofitholder`		LP	GLPK
Profit MDDF	`deaprofitmddf`		LP	GLPK
Profit Reverse DDF	`deaprofitrddf`	`:ERG`	LP	GLPK
Profit Reverse DDF	`deaprofitrddf`	`:MDDF`	LP	GLPK
Profit GDA	`deaprofitgda`		LP	GLPK
Profitability GDF	`deaprofitability`		NLP	Ipopt
Cost Radial	`deacost`		LP	GLPK
Cost Russell	`deacostrussell`		LP	GLPK
Cost Additive	`deacostadd`		LP	GLPK
Cost DDF	`deacostddf`		LP	GLPK
Cost Hölder	`deacostholder`		LP	GLPK
Cost Reverse DDF	`deacostrddf`		LP	GLPK
Cost GDA	`deacostgda`		LP	GLPK
Revenue Radial	`dearevenue`		LP	GLPK
Revenue Russell	`dearevenuerussell`		LP	GLPK
Revenue Additive	`dearevenueadd`		LP	GLPK
Revenue DDF	`dearevenueddf`		LP	GLPK
Revenue Hölder	`dearevenueholder`		LP	GLPK
Revenue Reverse DDF	`dearevenuerddf`		LP	GLPK
Revenue GDA	`dearevenuegda`		LP	GLPK

Where:

LP = Linear programming.
NLP = Nonlinear programming.

Models can be solved using a different optimizer by passing a DEAOptimizer object to the optimizer optional argument. For instruction, see the documentation on the DataEnvelopmentAnalysis package.