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Fraction-to-boundary steps preserve positivity and exact primal-dual feasibility certifies a gap
Statement
In symmetric-cone mode of Finite-budget primal-dual Newton methods for LP, convex QP, and symmetric cones, let be strictly interior primal and dual cone variables and let be their largest boundary-preserving step fractions. If , , and , then keeps both updated cone variables interior. The conservative fractions in the algorithm's Lorentz and PSD branches satisfy these inequalities. For any exactly primal- and dual-feasible conic pair, the gap is a rigorous upper bound on primal suboptimality.
In LP/QP mode, the coordinate fraction-to-boundary formula keeps . For the convex QP of that algorithm, if is primal feasible, , is free, and the exact stationarity residual vanishes, then For LP/QP iterates with full-row-rank , , and , the exact Newton matrix is nonsingular. Thus a requested gap is certified only under exact feasibility and stationarity conditions. Nonzero residual tolerances alone are not a certificate. Every finite iteration cap returns a status after finitely many bounded updates; a failure status proves no infeasibility claim.
Facts & Assumptions
Given: The proper-cone modes, fraction formulas, exact residual audits, and Lagrangians in the algorithm and conic model.
For conic primal and dual feasible variables, (Conic, LP, and convex QP primal-dual models).
A proper cone is closed and convex, and (Conic, LP, and convex QP primal-dual models).
The QP Lagrangian is (Conic, LP, and convex QP primal-dual models).
Every primal feasible point and dual feasible pair satisfy (Every Lagrangian dual feasible pair is a lower-bound certificate).
A differentiable convex function lies above its tangent plane (Differentiable convex functions are characterized by the gradient inequality).
The LP/QP primal-dual Newton matrix has trivial kernel under , full-row-rank , and (The LP/QP primal-dual Newton matrix is nonsingular from a strict positive start).
A real symmetric matrix has an orthonormal eigenbasis (Real spectral theorem: a self-adjoint endomorphism of a finite-dimensional real inner product space has an orthonormal eigenbasis), so its spectral norm is at most its Frobenius norm.
Proof
Because is interior, a small positive segment from in direction remains in . The set of feasible fractions in is closed by [F2], so its maximum is attained and . Any has , and the update is . An open ball about lies in ; scaling that ball by and adding shows the updated point is interior. The same argument applies to in . In the orthant, the coordinate-ratio formula is the maximal nonnegative boundary fraction. For a negative coordinate direction, gives ; nonnegative directions preserve positivity, and the same two cases apply to .
For a Lorentz factor, write and , with . Set and . If the step is unchanged. Otherwise , while . The algorithm's safe fraction therefore gives with . The triangle inequality then yields , so the updated Lorentz vector is interior. For a PSD factor and symmetric direction , let as in the algorithm, where . If , then . Otherwise set . Submultiplicativity of the operator norm and [F7] give . Since , , and for every nonzero , . Thus . The same bounds apply separately to primal and dual factors, so each computed safe fraction is no larger than its maximal boundary-preserving fraction.
For any feasible conic pair, [F1] and [F2] give . Taking the infimum over primal feasible and the supremum over dual feasible pairs shows that a feasible dual value is a lower bound on . Hence a computed primal-dual feasible pair with exact gap is an -suboptimality certificate.
In LP/QP mode, exact , , , and make . To apply [F4], use the smooth inequality convention , multiplier , and equality multiplier . Since , is convex, so [F5] implies for every ; therefore . By [F4], , and primal feasibility gives . Thus .
In LP/QP mode, [F6] supplies a unique exact Newton direction under the stated rank and strict-interiority hypotheses. Symmetric-cone mode may have a singular derivative, which the algorithm tests and reports.
Every dimension-bounded loop terminates after finitely many operations, and the outer loop increments its update counter until it reaches the finite cap or returns an earlier status. Therefore every invocation terminates with one of its declared statuses. A tolerance status based on nonzero residuals is explicitly residual-candidate, so no step above treats it as a certificate.
Depends on
- Finite-budget primal-dual Newton methods for LP, convex QP, and symmetric cones
- Conic, LP, and convex QP primal-dual models
- Finite-dimensional convex program, Lagrangian dual, and Slater condition
- The LP/QP primal-dual Newton matrix is nonsingular from a strict positive start
- Differentiable convex functions are characterized by the gradient inequality
- Every Lagrangian dual feasible pair is a lower-bound certificate
- Real spectral theorem: a self-adjoint endomorphism of a finite-dimensional real inner product space has an orthonormal eigenbasis
Used by
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Sources
- Stephen Boyd and Lieven Vandenberghe, Convex Optimization (standard reference, not scraped)
- Hamza Fawzi, Topics in Convex Optimisation, Lecture 16 (standard reference, not scraped)