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Merge pull request #142 from JuliaOpt/sddpcleaning
New interface for SDDP
2 parents f68b9da + c2b64ec commit e1ce8c0

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.travis.yml

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script:
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- if [[ -a .git/shallow ]]; then git fetch --unshallow; fi
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- julia -e 'Pkg.clone(pwd()); Pkg.build("StochDynamicProgramming"); Pkg.test("StochDynamicProgramming"; coverage=true)'
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before_script:
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- julia -e 'Pkg.clone("https://github.com/JuliaPolyhedra/CutPruners.jl")'
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- julia -e 'Pkg.clone("https://github.com/blegat/StochasticDualDynamicProgramming.jl")'
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after_success:
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- echo $TRAVIS_JULIA_VERSION
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- julia -e 'Pkg.add("Coverage"); cd(Pkg.dir("StochDynamicProgramming")); using Coverage; Coveralls.submit(Coveralls.process_folder()); Codecov.submit(Codecov.process_folder())'

README.md

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- Linear dynamics
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- Linear or convex piecewise linear cost
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Extension to non-linear formulation are under development.
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Extension to non-linear formulation are under development.
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Extension to more complex alea dependance are under developpment.
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## Why Extensive formulation ?
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An extensive formulation approach consists in representing the stochastic problem as a deterministic
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one with more variable and call a standard deterministic solver. Mainly usable in a linear
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one with more variable and call a standard deterministic solver. Mainly usable in a linear
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setting. Computational complexity is exponential in the number of stages.
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## Why Stochastic Dynamic Programming ?
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## Installation
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Installing StochDynamicProgramming is an easy process. Open Julia and enter
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Installing StochDynamicProgramming is an easy process.
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Currently, the package depends upon `CutPruners.jl`, which is not
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yet registered in Julia's METADATA. To install the package,
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open Julia and enter
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```julia
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julia> Pkg.update()
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julia> Pkg.clone("https://github.com/JuliaPolyhedra/CutPruners.jl")
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julia> Pkg.clone("https://github.com/blegat/StochasticDualDynamicProgramming.jl")
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julia> Pkg.add("StochDynamicProgramming")
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```

REQUIRE

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ProgressMeter
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Interpolations
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Iterators
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CutPruners
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StochasticDualDynamicProgramming

TODO.md

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