DualDecomposition.DualDecomposition — ModuleDualDecompositionThis module implements a block model for dual Decomposition and Lagrangian dual method for solving the block model. Applications of the dual Decomposition include stochastic programming, temporal decomposition, and network decomposition.
DualDecomposition.AbstractBlockModel — TypeBlockModelBlock model struture contrains a set of JuMP.Model objects, each of which represents a sub-block model with the information of how to couple these block models.
DualDecomposition.AbstractLagrangeMaster — TypeAbstractLagrangeMasterAbstract type of Lagrangian master methods
DualDecomposition.BundleMaster — TypeBundleMasterBundle method implementation of Lagrangian master method. This simply uses BundleMethod.jl package.
Arguments
constructor: struct for bundle methodoptimizer: optimization solver for bundle masterinner: bundle method object
DualDecomposition.CouplingVariableKey — TypeCouplingVariableKeyKey to map oupling variables. block_id identifies the problem block containing the variable, and coupling_id identifies a set of variables whose values are equal.
DualDecomposition.CouplingVariableRef — TypeCouplingVariableRefCoupling variable reference with key::CouplingVariableKey.
DualDecomposition.SubgradientMaster — TypeSubgradientMasterImplementation of projected subgradient method
DualDecomposition.add_block_model! — Methodadd_block_model!Add block model model to block_model::AbstractBlockModel with block_id.
DualDecomposition.add_constraints! — Methodadd_constraints!This function is to add any constraints to the master problem.
Arguments
LD: Lagrangian dualmethod: Lagrangian master
DualDecomposition.adjust_objective_function! — MethodThis adjusts the objective function of each Lagrangian subproblem.
DualDecomposition.block_model — Methodblock_modelThis returns a JuMP.Model object for a given block_id.
DualDecomposition.block_model — Methodblock_modelThis returns a dictionary of JuMP.Model objects.
DualDecomposition.block_solutions — Methodblock_solutionsThis returns a dictionary of JuMP.VariableRef solutions.
DualDecomposition.coupling_variables — Methodcoupling_variablesThis returns the array of coupling variables in block_model::AbstractBlockModel.
DualDecomposition.dual_objective_value — Methoddual_objective_valueThis returns the dual objective value obtained from a method.
DualDecomposition.dual_solution — Methoddual_solutionThis returns a vector of dual solution obtained from a method.
DualDecomposition.get_objective — Methodget_objectiveThis returns the objective function value.
Arguments
method: Lagrangian master
DualDecomposition.get_solution — Methodget_solutionThis returns the Lagrangian master solution.
Arguments
method: Lagrangian master
DualDecomposition.get_times — Methodget_timesThis returns the solution times of Lagrangian master for all iterations.
Arguments
method: Lagrangian master
DualDecomposition.has_block_model — Methodhas_block_modelThis returns true if block_model::AbstractBlockModel has key block_id::Integer; false otherwise.
DualDecomposition.load! — Methodload!This function loads the Lagrangian dual problem to the master.
Arguments
method: Lagrangian master methodnum_coupling_variables: number of coupling variablesnum_blocks: number of blocks (or Lagrangian subproblems)eval_function: function pointer to evalute Lagrangian dual functionsinit_sol: initial solution of the Lagrangian master
DualDecomposition.num_blocks — Methodnum_blocksNumber of blocks in block_model::AbstractBlockModel
DualDecomposition.num_coupling_variables — Methodnum_coupling_variablesThis returns the number of coupling variables in block_model::AbstractBlockModel.
DualDecomposition.objective_function — MethodWrappers of other functions
DualDecomposition.primal_objective_value — Methodprimalobjectivevalue
This returns the best primal objective value obtained from a method.
DualDecomposition.primal_solution — Methodprimal_solution
This returns a vector of the best primal solution obtained from a method.
DualDecomposition.reoptimize! — MethodThis re-optimizes block models if not solved to local optimality
DualDecomposition.reset_objective_function! — MethodThis resets the objective function of each Lagrangian subproblem.
DualDecomposition.run! — Functionrun!This runs the Lagrangian dual method for solving the block model.
DualDecomposition.run! — Functionrun!Empty function for AbstractMethod
DualDecomposition.run! — Methodrun!This runs the Lagrangian master method.
Arguments
method: Lagrangian master
DualDecomposition.run! — Methodrun!This run a heuristic that simply fixes the coupling variable values.
DualDecomposition.run! — Methodrun!This run a rounding heuristic.
DualDecomposition.set_block_weights! — Methodset_block_weights!
set the weights of the blocks that will be used by the primal heuristicsDualDecomposition.set_coupling_variables! — Methodset_coupling_variables!This sets coupling variables variables to block_model::AbstractBlockModel.
DualDecomposition.set_obj_limit! — Methodsetobjlimit!
This sets the Lagrangian bound limit.
Arguments
method: Lagrangian masterval: objective limit value
DualDecomposition.set_variables_by_couple! — Methodset_variables_by_couple!This sets BlockModel.variables_by_couple.
DualDecomposition.solve_sub_block! — MethodThis wraps the steps to optimize a block problem.
DualDecomposition.write_file! — Methodwrite_file!This function writes a vector to a file.
Arguments
v: vector to writename: file namedir: optional argument to give path to the file