Crash
Documentation for StochasticPrograms.jl
's crash methods, for use in structured solvers and sample-based solvers.
Index
StochasticPrograms.Crash
StochasticPrograms.Crash.Custom
StochasticPrograms.Crash.EVP
StochasticPrograms.Crash.FeasiblePoint
StochasticPrograms.Crash.None
StochasticPrograms.Crash.PreSolve
StochasticPrograms.Crash.Scenario
Crash methods
StochasticPrograms.Crash
— ModuleCrash
Collection of crash methods used to generate initial decisions in structured algorithms.
...
Available crash methods
...
Examples
The following solves a stochastic program sp
created in StochasticPrograms.jl
using an L-shaped algorithm with trust-region and Clp as an lpsolver
and by generating an initial decision with the EVP
crash.
julia> optimize!(sp, solver = LShapedSolver(GLPKSolverLP(), crash=Crash.EVP(), regularize = TrustRegion()))
L-Shaped Gap Time: 0:00:00 (8 iterations)
Objective: -855.8333333333339
Gap: 0.0
Number of cuts: 4
Iterations: 8
:Optimal
StochasticPrograms.Crash.Custom
— TypeCustom(x₀)
Use the user-supplied x₀
as initial decision.
StochasticPrograms.Crash.EVP
— TypeEVP
Solve the expected value problem corresponding to the stochastic program and use the expected value solution as initial decision.
StochasticPrograms.Crash.FeasiblePoint
— TypeFeasiblePoint
Generate a feasible first-stage decision as initial decision.
StochasticPrograms.Crash.None
— TypeNone
Randomize the initial decision (default).
StochasticPrograms.Crash.PreSolve
— TypePreSolve
Run a provided (ideally suboptimal) optimization procedure and use the (sub)optimal solution as initial decision.
StochasticPrograms.Crash.Scenario
— TypeScenario
Solve the wait-and-see problem corresponding a supplied scenario and use the optimal solution as initial decision.