问题
I'm trying to use JuMP to solve a non-linear problem, where the number of variables are decided by the user - that is, not known at compile time.
To accomplish this, the @NLobjective
line looks like this:
@eval @JuMP.NLobjective(m, Min, $(Expr(:call, :myf, [Expr(:ref, :x, i) for i=1:n]...)))
Where, for instance, if n=3
, the compiler interprets the line as identical to:
@JuMP.NLobjective(m, Min, myf(x[1], x[2], x[3]))
The issue is that @eval
works only in the global scope, and when contained in a function, an error is thrown.
My question is: how can I accomplish this same functionality -- getting @NLobjective
to call myf
with a variable number of x[1],...,x[n]
arguments -- within the local, not-known-at-compilation scope of a function?
def testme(n)
myf(a...) = sum(collect(a).^2)
m = JuMP.Model(solver=Ipopt.IpoptSolver())
JuMP.register(m, :myf, n, myf, autodiff=true)
@JuMP.variable(m, x[1:n] >= 0.5)
@eval @JuMP.NLobjective(m, Min, $(Expr(:call, :myf, [Expr(:ref, :x, i) for i=1:n]...)))
JuMP.solve(m)
end
testme(3)
Thanks!
回答1:
As explained in http://jump.readthedocs.io/en/latest/nlp.html#raw-expression-input , objective functions can be given without the macro. The relevant expression:
JuMP.setNLobjective(m, :Min, Expr(:call, :myf, [x[i] for i=1:n]...))
is even simpler than the @eval
based one and works in the function. The code is:
using JuMP, Ipopt
function testme(n)
myf(a...) = sum(collect(a).^2)
m = JuMP.Model(solver=Ipopt.IpoptSolver())
JuMP.register(m, :myf, n, myf, autodiff=true)
@JuMP.variable(m, x[1:n] >= 0.5)
JuMP.setNLobjective(m, :Min, Expr(:call, :myf, [x[i] for i=1:n]...))
JuMP.solve(m)
return [getvalue(x[i]) for i=1:n]
end
testme(3)
and it returns:
julia> testme(3)
:
EXIT: Optimal Solution Found.
3-element Array{Float64,1}:
0.5
0.5
0.5
来源:https://stackoverflow.com/questions/44710900/juliajump-variable-number-of-arguments-to-function