Updating solve.jl

Project.toml

@@ -1,6 +1,6 @@
 name = "COBRA"
 uuid = "58298e0b-d05c-52ec-a210-0694647ebfc7"
-version = "0.4.1"
+version = "0.4.2"
 
 [deps]
 CPLEX = "a076750e-1247-5638-91d2-ce28b192dca0"

src/solve.jl

@@ -145,128 +145,6 @@ function linprog(c, A, sense, b, l, u, solver)
     )
 end
 
-#-------------------------------------------------------------------------------------------
-"""
-    buildlp(c, A, sense, b, l, u, solver)
-
-Function used to build a model using JuMP.
-
-# INPUTS
-
-- `c`:           The objective vector, always in the sense of minimization
-- `A`:           Constraint matrix
-- `sense`:       Vector of constraint sense characters '<', '=', and '>'
-- `b`:           Right-hand side vector
-- `l`:           Vector of lower bounds on the variables
-- `u`:           Vector of upper bounds on the variables
-- `solver`:      A `::SolverConfig` object that contains a valid `handle`to the solver
-
-# OUTPUTS
-
-- `model`:       An `::LPproblem` object that has been built using the JuMP.
-- `x`:           Primal solution vector
-
-# EXAMPLES
-
-```julia
-julia> model, x = buildlp(c, A, sense, b, l, u, solver)
-```
-
-"""
-
-function buildlp(c, A, sense, b, l, u, solver)
-    N = length(c)
-    model = Model(solver)
-    x = @variable(model, l[i] <= x[i=1:N] <= u[i])
-    @objective(model, Min, c' * x)
-    eq_rows, ge_rows, le_rows = sense .== '=', sense .== '>', sense .== '<'
-    @constraint(model, A[eq_rows, :] * x .== b[eq_rows])
-    @constraint(model, A[ge_rows, :] * x .>= b[ge_rows])
-    @constraint(model, A[le_rows, :] * x .<= b[le_rows])
-    return model, x, c
-end
-
-#-------------------------------------------------------------------------------------------
-"""
-    solvelp(model, x)
-
-Function used to solve a LPproblem using JuMP.
-
-# INPUTS
-
-- `model`:       An `::LPproblem` object that has been built using the JuMP.
-- `x`:           Primal solution vector
-
-# OUTPUTS
-
-- `status`:      Termination status
-- `objval`:      Optimal objective value
-- `sol`:         Primal solution vector
-
-# EXAMPLES
-
-```julia
-julia> status, objval, sol = solvelp(model, x)
-```
-
-"""
-
-function solvelp(model, x)
-    optimize!(model)
-    return (
-        status = termination_status(model),
-        objval = objective_value(model),
-        sol = value.(x)
-    )
-end
-
-#-------------------------------------------------------------------------------------------
-"""
-    linprog(c, A, sense, b, l, u, solver)
-
-Function used to build and solve a LPproblem using JuMP.
-
-# INPUTS
-
-- `c`:           The objective vector, always in the sense of minimization
-- `A`:           Constraint matrix
-- `sense`:       Vector of constraint sense characters '<', '=', and '>'
-- `b`:           Right-hand side vector
-- `l`:           Vector of lower bounds on the variables
-- `u`:           Vector of upper bounds on the variables
-- `solver`:      A `::SolverConfig` object that contains a valid `handle`to the solver
-
-# OUTPUTS
-
-- `status`:      Termination status
-- `objval`:      Optimal objective value
-- `sol`:         Primal solution vector
-
-# EXAMPLES
-
-```julia
-julia> status, objval, sol = linprog(c, A, sense, b, l, u, solver)
-```
-
-"""
-
-function linprog(c, A, sense, b, l, u, solver)
-    N = length(c)
-    model = Model(solver)
-    @variable(model, l[i] <= x[i=1:N] <= u[i])
-    @objective(model, Min, c' * x)
-    eq_rows, ge_rows, le_rows = sense .== '=', sense .== '>', sense .== '<'
-    @constraint(model, A[eq_rows, :] * x .== b[eq_rows])
-    @constraint(model, A[ge_rows, :] * x .>= b[ge_rows])
-    @constraint(model, A[le_rows, :] * x .<= b[le_rows])
-    optimize!(model)
-    return (
-        status = termination_status(model),
-        objval = objective_value(model),
-        sol = value.(x)
-    )
-end
-
 #-------------------------------------------------------------------------------------------
 """
     buildCobraLP(model, solver)
@@ -360,7 +238,7 @@ function changeCobraSolver(name, params=[]; printLevel::Int=1)
             if abs(printLevel) > 1
                 printLevel = 1
             end
-            solver.handle = CplexSolver(CPX_PARAM_SCRIND=printLevel)
+            solver.handle = CPLEX.Optimizer
         catch
             error("The solver `CPLEX` cannot be set using `changeCobraSolver()`.")
         end
@@ -373,7 +251,7 @@ function changeCobraSolver(name, params=[]; printLevel::Int=1)
                 solver.handle = GLPK.Optimizer
             end
         catch
-            error("The solver `GLPK` or `GLPKMathProgInterface` cannot be set using `changeCobraSolver()`.")
+            error("The solver `GLPK` cannot be set using `changeCobraSolver()`.")
         end
 
     elseif name == "Gurobi"