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| <html lang="en"><head><meta charset="UTF-8"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><title>Readings · SDDP.jl</title><link href="https://cdnjs.cloudflare.com/ajax/libs/normalize/4.2.0/normalize.min.css" rel="stylesheet" type="text/css"/><link href="https://fonts.googleapis.com/css?family=Lato|Roboto+Mono" rel="stylesheet" type="text/css"/><link href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/4.6.3/css/font-awesome.min.css" rel="stylesheet" type="text/css"/><link href="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/styles/default.min.css" rel="stylesheet" type="text/css"/><script>documenterBaseURL="."</script><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.2.0/require.min.js" data-main="assets/documenter.js"></script><script src="siteinfo.js"></script><script src="../versions.js"></script><link href="assets/documenter.css" rel="stylesheet" type="text/css"/><link href="assets/custom.css" rel="stylesheet" type="text/css"/></head><body><nav class="toc"><h1>SDDP.jl</h1><select id="version-selector" onChange="window.location.href=this.value" style="visibility: hidden"></select><form class="search" action="search.html"><input id="search-query" name="q" type="text" placeholder="Search docs"/></form><ul><li><a class="toctext" href="index.html">Manual</a></li><li class="current"><a class="toctext" href="readings.html">Readings</a><ul class="internal"><li><a class="toctext" href="#Stochastic-Optimization-1">Stochastic Optimization</a></li><li><a class="toctext" href="#Stochastic-Dual-Dynamic-Programming-1">Stochastic Dual Dynamic Programming</a></li><li><a class="toctext" href="#Julia-1">Julia</a></li><li><a class="toctext" href="#JuMP-1">JuMP</a></li></ul></li><li><a class="toctext" href="apireference.html">Reference</a></li></ul></nav><article id="docs"><header><nav><ul><li><a href="readings.html">Readings</a></li></ul><a class="edit-page" href="https://github.com/odow/SDDP.jl/tree/39f13029b5bb7b8b2c1ed5d8b7f7ec0f266181ee/docs/src/readings.md"><span class="fa"></span> Edit on GitHub</a></nav><hr/><div id="topbar"><span>Readings</span><a class="fa fa-bars" href="#"></a></div></header><p>On this page, we've collated a variety of papers and books we think are helpful readings that cover knowledge needed to use SDDP.jl.</p><h2><a class="nav-anchor" id="Stochastic-Optimization-1" href="#Stochastic-Optimization-1">Stochastic Optimization</a></h2><p>A general primer on Stochastic Programming</p><ul><li><p>Birge, J.R., Louveaux, F., 2011. Introduction to Stochastic Programming, Springer Series in Operations Research and Financial Engineering. Springer New York, New York, NY. <a href="https://link.springer.com/book/10.1007%2F978-1-4614-0237-4">doi:10.1007/978-1-4614-0237-4</a></p></li></ul><p>Some overviews of Stochastic Optimization and where it sits in relation to other fields</p><ul><li><p>Powell, W.B., 2014. Clearing the Jungle of Stochastic Optimization, in: Newman, A.M., Leung, J., Smith, J.C., Greenberg, H.J. (Eds.), Bridging Data and Decisions. INFORMS, pp. 109–137. <a href="http://adp.princeton.edu/Papers/Powell-ClearingtheJungleofStochasticOptimizationOctober2014.pdf">link</a></p></li></ul><ul><li><p>Powell, W.B., 2016. A Unified Framework for Optimization under Uncertainty TutORials in Operations Research, in: Optimization Challenges in Complex, Networked and Risky Systems. pp. 45–83. <a href="http://castlelab.princeton.edu/html/Papers/Powell-UnifiedFrameworkforStochasticOptimization_April162016.pdf">link</a></p></li></ul><h2><a class="nav-anchor" id="Stochastic-Dual-Dynamic-Programming-1" href="#Stochastic-Dual-Dynamic-Programming-1">Stochastic Dual Dynamic Programming</a></h2><p>The original paper presenting SDDP</p><ul><li><p>Pereira, M.V.F., Pinto, L.M.V.G., 1991. Multi-stage stochastic optimization applied to energy planning. Mathematical Programming 52, 359–375. <a href="https://link.springer.com/article/10.1007/BF01582895">doi:10.1007/BF01582895</a></p></li></ul><p>The paper presenting the Markov version of SDDP implemented in this library</p><ul><li><p>Philpott, A.B., de Matos, V.L., 2012. Dynamic sampling algorithms for multi-stage stochastic programs with risk aversion. European Journal of Operational Research 218, 470–483. <a href="http://www.sciencedirect.com/science/article/pii/S0377221711010332">doi:10.1016/j.ejor.2011.10.056</a></p></li></ul><h2><a class="nav-anchor" id="Julia-1" href="#Julia-1">Julia</a></h2><p>The organisation's website</p><ul><li><p><a href="https://julialang.org/">https://julialang.org/</a></p></li></ul><p>The paper describing Julia</p><ul><li><p>Bezanson, J., Edelman, A., Karpinski, S., Shah, V.B., 2017. Julia: A Fresh Approach to Numerical Computing. SIAM Review 59, 65–98. <a href="http://epubs.siam.org/doi/abs/10.1137/141000671">doi:10.1137/141000671</a></p></li></ul><h2><a class="nav-anchor" id="JuMP-1" href="#JuMP-1">JuMP</a></h2><p>Source code on Github</p><ul><li><p>[www.github.com/JuliaOpt/JuMP.jl]((https://www.github.com/JuliaOpt/JuMP.jl)</p></li></ul><p>The paper describing JuMP</p><ul><li><p>Dunning, I., Huchette, J., Lubin, M., 2017. JuMP: A Modeling Language for Mathematical Optimization. SIAM Review 59, 295–320. <a href="http://epubs.siam.org/doi/pdf/10.1137/15M1020575">doi:10.1137/15M1020575</a></p></li></ul><footer><hr/><a class="previous" href="index.html"><span class="direction">Previous</span><span class="title">Manual</span></a><a class="next" href="apireference.html"><span class="direction">Next</span><span class="title">Reference</span></a></footer></article></body></html> |
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