Compatibility with JuMP 0.21

- Compatibility with JuMP 0.21
- Set package version to 0.1.2.

NEWS.md

@@ -1,6 +1,12 @@
 DataEnvelopmentAnalysis.jl release notes
 ========================================
 
+Version 0.1.2 (Feb 25, 2020)
+----------------------------
+- Compatibility with JuMP 0.21.
+- Weak disposal in radial, cost, and revenue models.
+- Minor bugs fixed.
+
 Version 0.1.1 (Oct 29, 2019)
 ----------------------------
 

Project.toml

@@ -1,7 +1,7 @@
 name = "DataEnvelopmentAnalysis"
 uuid = "a100299e-89d6-11e9-0fa0-2daf497e6a05"
 authors = ["Javier Barbero <jbarberoeco@gmail.com>"]
-version = "0.1.1"
+version = "0.1.2"
 
 [deps]
 GLPK = "60bf3e95-4087-53dc-ae20-288a0d20c6a6"
@@ -17,7 +17,7 @@ StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 julia = "1"
 GLPK = "0.12"
 Ipopt = "0.6"
-JuMP = "0.20"
+JuMP = "0.21"
 StatsBase = "0.32"
 
 [extras]

src/dea.jl

@@ -105,7 +105,8 @@ function dea(X::Matrix, Y::Matrix; orient::Symbol = :Input, rts::Symbol = :CRS,
         y0 = Y[i,:]
 
         # Create the optimization model
-        deamodel = Model(with_optimizer(GLPK.Optimizer))
+        deamodel = Model(GLPK.Optimizer)
+
         @variable(deamodel, eff)
         @variable(deamodel, lambda[1:nref] >= 0)
 

src/deaadd.jl

@@ -136,7 +136,8 @@ function deaadd(X::Matrix, Y::Matrix, model::Symbol = :Default; rts::Symbol = :V
         wY0 = wY[i,:]
 
         # Create the optimization model
-        deamodel = Model(with_optimizer(GLPK.Optimizer))
+        deamodel = Model(GLPK.Optimizer)
+
         @variable(deamodel, sX[1:m] >= 0)
         @variable(deamodel, sY[1:s] >= 0)
         @variable(deamodel, lambda[1:nref] >= 0)

src/deacost.jl

@@ -81,7 +81,8 @@ function deacost(X::Matrix, Y::Matrix, W::Matrix; rts::Symbol = :VRS, disposal::
         w0 = W[i,:]
 
         # Create the optimization model
-        deamodel = Model(with_optimizer(GLPK.Optimizer))
+        deamodel = Model(GLPK.Optimizer)
+
         @variable(deamodel, Xeff[1:m])
         @variable(deamodel, lambda[1:n] >= 0)
 

src/deaddf.jl

@@ -98,7 +98,8 @@ function deaddf(X::Matrix, Y::Matrix, Gx::Matrix, Gy::Matrix; rts::Symbol = :CRS
         Gy0 = Gy[i,:]
 
         # Create the optimization model
-        deamodel = Model(with_optimizer(GLPK.Optimizer))
+        deamodel = Model(GLPK.Optimizer)
+
         @variable(deamodel, eff)
         @variable(deamodel, lambda[1:nref] >= 0)
 

src/deagdf.jl

@@ -81,7 +81,10 @@ function deagdf(X::Matrix, Y::Matrix, alpha::Float64; rts::Symbol = :CRS, slack
         y0 = Y[i,:]
 
         # Create the optimization model
-        deamodel = Model(with_optimizer(Ipopt.Optimizer, print_level = 0))
+        deamodel = Model(Ipopt.Optimizer)
+        set_silent(deamodel)
+        set_optimizer_attribute(deamodel, "print_level", 0)
+
         @variable(deamodel, eff, start = 1.0)
         @variable(deamodel, lambda[1:nref] >= 0)
 

src/deaprofit.jl

@@ -97,7 +97,8 @@ function deaprofit(X::Matrix, Y::Matrix, W::Matrix, P::Matrix, Gx::Matrix, Gy::M
         p0 = P[i,:]
 
         # Create the optimization model
-        deamodel = Model(with_optimizer(GLPK.Optimizer))
+        deamodel = Model(GLPK.Optimizer)
+
         @variable(deamodel, Xeff[1:m])
         @variable(deamodel, Yeff[1:s])
         @variable(deamodel, lambda[1:n] >= 0)

src/deaprofitability.jl

@@ -88,7 +88,10 @@ function deaprofitability(X::Matrix, Y::Matrix, W::Matrix, P::Matrix; alpha::Flo
         p0 = P[i,:]
 
         # Create the optimization model
-        deamodel = Model(with_optimizer(Ipopt.Optimizer, print_level= 0 ))
+        deamodel = Model(Ipopt.Optimizer)
+        set_silent(deamodel)
+        set_optimizer_attribute(deamodel, "print_level", 0)
+
         @variable(deamodel, eff, start = 1.0)
         @variable(deamodel, lambda[1:n] >= 0)
 

src/dearevenue.jl

@@ -81,7 +81,7 @@ function dearevenue(X::Matrix, Y::Matrix, P::Matrix; rts::Symbol = :VRS, disposa
         p0 = P[i,:]
 
         # Create the optimization model
-        deamodel = Model(with_optimizer(GLPK.Optimizer))
+        deamodel = Model(GLPK.Optimizer)
         @variable(deamodel, Yeff[1:s])
         @variable(deamodel, lambda[1:n] >= 0)