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AmplNLReader.AmplNLPMeta
— TypeAmplNLPMeta <: AbstractNLPModelMeta
A composite type that represents the main features of the optimization problem
optimize obj(x)
subject to lvar ≤ x ≤ uvar
lcon ≤ cons(x) ≤ ucon
where x
is an nvar
-dimensional vector, obj
is the real-valued objective function, cons
is the vector-valued constraint function, optimize
is either "minimize" or "maximize".
Here, lvar
, uvar
, lcon
and ucon
are vectors. Some of their components may be infinite to indicate that the corresponding bound or general constraint is not present.
AmplNLPMeta(nvar; kwargs...)
Create an AmplNLPMeta
with nvar
variables. The following keyword arguments are accepted:
x0
: initial guesslvar
: vector of lower boundsuvar
: vector of upper boundsnbv
: number of linear binary variablesniv
: number of linear non-binary integer variablesnlvb
: number of nonlinear variables in both objectives and constraintsnlvo
: number of nonlinear variables in objectives (includes nlvb)nlvc
: number of nonlinear variables in constraints (includes nlvb)nlvbi
: number of integer nonlinear variables in both objectives and constraintsnlvci
: number of integer nonlinear variables in constraints onlynlvoi
: number of integer nonlinear variables in objectives onlynwv
: number of linear network (arc) variablesncon
: number of general constraintsy0
: initial Lagrange multiplierslcon
: vector of constraint lower boundsucon
: vector of constraint upper boundsnnzo
: number of nonzeros in all objectives gradientsnnzj
: number of elements needed to store the nonzeros in the sparse Jacobianlin_nnzj
: number of elements needed to store the nonzeros in the sparse Jacobian of linear constraintsnln_nnzj
: number of elements needed to store the nonzeros in the sparse Jacobian of nonlinear constraintsnnzh
: number of elements needed to store the nonzeros in the sparse Hessiannlin
: number of linear constraintsnnln
: number of nonlinear general constraintsnnnet
: number of nonlinear network constraintsnlnet
: number of linear network constraintslin
: indices of linear constraintsnln
: indices of nonlinear constraintsnnet
: indices of nonlinear network constraintslnet
: indices of linear network constraintsminimize
: true if optimize == minimizenlo
: number of nonlinear objectivesislp
: true if the problem is a linear programname
: problem name