Cone programming
Cone programs are optimization problems that minimize a linear functional over the intersection of an affine subspace and a convex cone :
\[ \begin{aligned} \text{minimize} \quad & \langle c, x \rangle \\ \text{subject to} \quad & Ax=b \\ & x \in \mathcal{K} \end{aligned} \]
Any convex constraint can be represented as a conic constraint, so not every cone program is efficiently solvable. Even so, many commonly occurring cones give rise to tractable optimization problems, making cone programming a useful unifying framework.
Convex cone | Cone program |
---|---|
\(\mathbb{R}^n_+\), the nonnegative orthant | Linear program (LP) |
\(\mathcal{Q}^n\), the quadratic (ice cream) cone | Second-order cone program (SOCP) |
\(\mathcal{S}^n_+\), the cone of PSD matrices | Semidefinite program (SDP) |
Exponential cone | Geometric program |
Cone of copositive matrices | Copositive program |
General cone programs
- Ben-Tal & Nemirovski, 2001: Lectures on modern convex optimization (doi)
- Renegar, 2001: A mathmatical view of interior point methods, Ch. 3: Conic programming and duality (doi)
- Boyd & Vandenberghe, 2004: Convex optimization (pdf), Sec. 4.6: Generalized inequality constraints
- Vandenberghe, 2016, lecture notes: Conic optimization (pdf)
Geometric programs
Cone programs based on the exponential cone and its reparametrization, the relative entropy cone.
- Chandrasekaran & Shah, 2014: Conic geometric programming (doi, arxiv)
- Not having read the paper, I don’t see how this is any more general than cone programming over a product cone of the exponential cone and another convex cone
- Chandrasekaran & Shah, 2016, expository paper: Relative entropy optimization and its applications (doi)
Copositive programs
Hyperbolic programs
Hyperbolic programming includes semidefinite (and thus also linear and second-order cone) programming) as a special case.
- Renegar, 2006: Hyperbolic programs, and their derivative relaxations (doi)
- Renegar, 2019: Accelerated first-order methods for hyperbolic programming (doi, arxiv)
For more recent work, see the 2019 Simons Workshop on Hyperbolic Polynomials and Hyperbolic Programming.