How should I think about the differences between stochastic optimization (SO) and stochastic programming (SP)? From Wikipedia, it seems that SO is a framework that uses randomness to solve a pre-existing optimization problem whereas SP uses randomness to formulate an optimization problem.

If this is appropriate, then how does robust optimization (RO), which I might call robust programming in light of Wikipedia's SO/SP pages, fit in? It seems that SP makes use of probabilistic tools to work with explicit (distributional form) representations of uncertainty whereas RP assumes makes no explicit use of probabilistic tools outside of assuming known support for an uncertainty set. Is this the primary distinction? Is there a way to view RP as a subclass of SP problems?

asked 18 Dec '17, 17:05

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jjjjjj
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Asked: 18 Dec '17, 17:05

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Last updated: 18 Dec '17, 17:05

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