On semidefinite programming relaxations for a class of robust SOS-convex polynomial optimization problems

Related Items (1)

Cites Work

Some applications of polynomial optimization in operations research and real-time decision making
Dual semidefinite programs without duality gaps for a class of convex minimax programs
A convex polynomial that is not sos-convex
Finding efficient solutions in robust multiple objective optimization with SOS-convex polynomial data
Semidefinite representation of convex sets
Applications of second-order cone programming
Second-order cone programming
On minimizing difference of a SOS-convex polynomial and a support function over a SOS-concave matrix polynomial constraint
Radius of robust feasibility formulas for classes of convex programs with uncertain polynomial constraints
Some geometric results in semidefinite programming
Exact SDP relaxations for classes of nonlinear semidefinite programming problems
A hybrid approach for finding efficient solutions in vector optimization with SOS-convex polynomials
A new bounded degree hierarchy with SOCP relaxations for global polynomial optimization and conic convex semi-algebraic programs
A sufficient condition for asymptotically well behaved property of convex polynomials
Second-order cone programming relaxations for a class of multiobjective convex polynomial problems
Characterizing robust weak sharp solution sets of convex optimization problems with uncertainty
Robust SOS-convex polynomial optimization problems: exact SDP relaxations
Characterizing robust solution sets of convex programs under data uncertainty
Optimality conditions and duality for minimax fractional programming problems with data uncertainty
Some characterizations of robust solution sets for uncertain convex optimization problems with locally Lipschitz inequality constraints
Optimality conditions and duality for robust nonsmooth multiobjective optimization problems with constraints
On robust multiobjective optimization
Some characterizations of robust optimal solutions for uncertain fractional optimization and applications
Some characterizations of approximate solutions for robust semi-infinite optimization problems
Lectures on Modern Convex Optimization
WHAT IS...a Spectrahedron?
A Complete Characterization of the Gap between Convexity and SOS-Convexity
On the Lasserre Hierarchy of Semidefinite Programming Relaxations of Convex Polynomial Optimization Problems
Convexity in SemiAlgebraic Geometry and Polynomial Optimization
Semidefinite Optimization and Convex Algebraic Geometry
Generalized robust duality in constrained nonconvex optimization
On Radius of Robust Feasibility for Convex Conic Programs with Data Uncertainty
Global Error Bounds for Systems of Convex Polynomials over Polyhedral Constraints
Multicriteria Optimization
Linear Matrix Inequality Conditions and Duality for a Class of Robust Multiobjective Convex Polynomial Programs
DSOS and SDSOS Optimization: More Tractable Alternatives to Sum of Squares and Semidefinite Optimization
Convex Analysis
Characterizing robust optimal solution sets for nonconvex uncertain semi-infinite programming problems involving tangential subdifferentials

This page was built for publication: On semidefinite programming relaxations for a class of robust SOS-convex polynomial optimization problems