Second-order cone programming: Difference between revisions

Revision as of 10:18, 29 November 2023

Revision as of 10:51, 29 November 2023

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as deterministic second-order cone programs since data defining them are deterministic.

Stochastic second-order cone programs are a class of optimization problems that are defined to handle uncertainty in data defining deterministic second-order cone programs.<ref>{{Cite journal |last=Alzalg |first=Baha M. |date=2012-10-01 |title=Stochastic second-order cone programming: Applications models |url=https://www.sciencedirect.com/science/article/pii/S0307904X11008547 |journal=Applied Mathematical Modelling |language=en |volume=36 |issue=10 |pages=5122–5134 |doi=10.1016/j.apm.2011.12.053 |issn=0307-904X}}</ref>

=== Other examples ===

Other modeling examples are available at the MOSEK modeling cookbook.<ref>{{Cite web |title=MOSEK Modeling Cookbook - Conic Quadratic Optimization |url=https://docs.mosek.com/modeling-cookbook/cqo.html}}</ref>

==Solvers and scripting (programming) languages==

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|SCS (Splitting Conic Solver) is a numerical optimization package for solving large-scale convex quadratic cone problems.

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== See also ==

* [[Power cone]]<nowiki/>s are generalizations of quadratic cones to powers other than 2.<ref>{{Cite web |title=MOSEK Modeling Cookbook - the Power Cones |url=https://docs.mosek.com/modeling-cookbook/powo.html}}</ref>

==References==