OptimizationProblems.jl problem classification

It is possible to access information on the problems implemented in OptimizationProblems.jl without loading the problems using the package's own classification. ​

using OptimizationProblems

Each problem has its own metadata structure, and there is a global metadata structure regrouping all the information.

Problem's metadata

Each problem's metadata is accessible with OptimizationProblems.nameoftheproblem_meta and regroups in a Dict most of the essential information regarding each problem.

OptimizationProblems.AMPGO02_meta

Dict{Symbol, Any} with 22 entries:
  :has_equalities_only    => false
  :origin                 => :unknown
  :has_inequalities_only  => false
  :defined_everywhere     => missing
  :has_fixed_variables    => false
  :variable_ncon          => false
  :nvar                   => 1
  :is_feasible            => true
  :url                    => "http://infinity77.net/global_optimization/test_fu…
  :minimize               => true
  :ncon                   => 0
  :name                   => "AMPGO02"
  :origin_notes           => "Problem 2 in\nhttp://infinity77.net/global_optimi…
  :best_known_lower_bound => -Inf
  :lib                    => "AMPGO:2"
  :objtype                => :other
  :best_known_upper_bound => 0.839498
  :has_bounds             => false
  :reference              => "@misc{GavanaGOTestSuite,\n  author       = {Gavan…
  ⋮                       => ⋮

See ? OptimizationProblems.meta for more documentation on the various entries and their default values.

This structure is completed by getters to access the number of variables, get_nameoftheproblem_nvar, the number of constraints, get_nameoftheproblem_ncon, the number of linear constraints, get_nameoftheproblem_nlin, the number of nonlinear constraints, get_nameoftheproblem_nnln, the number of equality constraints, get_nameoftheproblem_nequ, and the number of inequality constraints, get_nameoftheproblem_nineq.

OptimizationProblems.get_AMPGO02_nvar()

1

For scalable problems the entry :variable_nvar (and/or :variable_ncon) is set as true and one can access the number of variables by passing the parameters to the getter functions. By default, the number of variables set in the meta is obtained using OptimizationProblems.default_nvar as a parameter to define the problem.

OptimizationProblems.arglina_meta

Dict{Symbol, Any} with 22 entries:
  :has_equalities_only    => false
  :origin                 => :unknown
  :has_inequalities_only  => false
  :defined_everywhere     => missing
  :has_fixed_variables    => false
  :variable_ncon          => false
  :nvar                   => 100
  :is_feasible            => true
  :url                    => "https://doi.org/10.1145/355934.355936, https://bi…
  :minimize               => true
  :ncon                   => 0
  :name                   => "arglina"
  :origin_notes           => "Problem 32 in\nJ.J. More', B.S. Garbow and K.E. H…
  :best_known_lower_bound => -Inf
  :lib                    => "CUTEst:ARGLINA"
  :objtype                => :least_squares
  :best_known_upper_bound => 500.0
  :has_bounds             => false
  :reference              => "@article{MoreGarbowHillstrom1981,\n  author  = {M…
  ⋮                       => ⋮

OptimizationProblems.get_arglina_nvar(n = 10)

10

OptimizationProblems.PureJuMP.arglina(n = 10)

A JuMP Model
├ solver: none
├ objective_sense: MIN_SENSE
│ └ objective_function_type: JuMP.QuadExpr
├ num_variables: 10
├ num_constraints: 0
└ Names registered in the model
  └ :x

Global meta

This package collects all the metadata in a single DataFrame.

OptimizationProblems.meta