Julia MethodError: no method matching parseNLExpr_runtime(

Question

我正在尝试编写 here 中描述的方法来估计金属制造商的生产函数。我在 Python 和 Matlab 中完成了此操作，但我正在尝试学习 Julia。

spain_clean.csv是我加载的log capital（lnk）、log labor（lnl）、log output（lnva）、log material（lnm）的数据集。滞后变量在它们前面用 "l" 表示。

代码在底部。我收到一个错误：

ERROR: LoadError: MethodError: no method matching parseNLExpr_runtime(::JuMP.Model, ::JuMP.GenericQuadExpr{Float64,JuMP.Variable}, ::Array{ReverseDiffSparse.NodeData,1}, ::Int32, ::Array{Float64,1})

我认为这与在非线性中使用向量和和数组有关objective，但我对 Julia 的了解还不足以调试它。

using JuMP  # Need to say it whenever we use JuMP

using Clp, Ipopt # Loading the GLPK module for using its solver

using CSV # csv reader


# read data
df = CSV.read("spain_clean.csv")


#MODEL CONSTRUCTION
#--------------------

acf = Model(solver=IpoptSolver())



@variable(acf, -10<= b0  <= 10) # 

@variable(acf, -5 <= bk <= 5 ) # 

@variable(acf, -5 <= bl <= 5 ) #

@variable(acf, -10<= g1 <= 10) # 


const g = sum(df[:phihat]-b0-bk* df[:lnk]-bl* df[:lnl]-g1* (df[:lphihat]-b0-bk* df[:llnk]-bl* df[:llnl]))

const gllnk = sum((df[:phihat]-b0-bk* df[:lnk]-bl* df[:lnl]-g1* (df[:lphihat]-b0-bk* df[:llnk]-bl* df[:llnl])).*df[:llnk])

const gllnl = sum((df[:phihat]-b0-bk* df[:lnk]-bl* df[:lnl]-g1* (df[:lphihat]-b0-bk* df[:llnk]-bl* df[:llnl])).*df[:llnl])

const glphihat = sum((df[:phihat]-b0-bk* df[:lnk]-bl* df[:lnl]-g1* (df[:lphihat]-b0-bk* df[:llnk]-bl* df[:llnl])).*df[:lphihat])



#OBJECTIVE  

@NLobjective(acf, Min, g* g + gllnk* gllnk + gllnl* gllnk + glphihat* glphihat)



#SOLVE IT 
status = solve(acf) # solves the model

println("Objective value: ", getobjectivevalue(acf)) #     getObjectiveValue(model_name) gives the optimum objective value

println("b0 = ", getvalue(b0)) 

println("bk = ", getvalue(bk))

println("bl = ", getvalue(bl))

println("g1 = ", getvalue(g1))

Answer 1

不是 Julia 专家，但我认为您的代码有几处错误。首先，常数不应该在迭代过程中改变，你正在使它们成为控制变量的函数。其次，你想要使用的是非线性表达式而不是常量。所以你想写的不是常数而是

N = size(df, 1)

@NLexpression(acf, g, sum(df[i, :phihat]-b0-bk* df[i, :lnk]-bl* df[i, :lnl]-g1* (df[i, :lphihat]-b0-bk* df[i, :llnk]-bl* df[i, :llnl]) for i=1:N))

@NLexpression(acf, gllnk, sum((df[i,:phihat]-b0-bk* df[i,:lnk]-bl* df[i,:lnl]-g1* (df[i,:lphihat]-b0-bk* df[i,:llnk]-bl* df[i,:llnl]))*df[i,:llnk] for i=1:N))

@NLexpression(acf,gllnl,sum((df[i,:phihat]-b0-bk* df[i,:lnk]-bl* df[i,:lnl]-g1* (df[i,:lphihat]-b0-bk* df[i,:llnk]-bl* df[i,:llnl]))*df[i,:llnl] for i=1:N))

@NLexpression(acf,glphihat,sum((df[i,:phihat]-b0-bk* df[i,:lnk]-bl* df[i,:lnl]-g1* (df[i,:lphihat]-b0-bk* df[i,:llnk]-bl* df[i,:llnl]))*df[i,:lphihat] for i=1:N))

我测试了这个，它似乎有效。

Julia MethodError: no method matching parseNLExpr_runtime(

Julia MethodError: no method matching parseNLExpr_runtime(

economics

nonlinear-optimization

julia

julia-jump