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A distributional Farkas’ lemma and moment optimization problems with no-gap dual semi-definite programs
We present a generalized Farkas’ Lemma for an inequality system involving distributions. This lemma establishes an equivalence between an...
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Semi-definite Representations for Sets of Cubics on the Two-dimensional Sphere
The compact set of homogeneous quadratic polynomials in n real variables with modulus bounded by 1 on the unit sphere is trivially semi-definite...
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Primal-dual path following method for nonlinear semi-infinite programs with semi-definite constraints
In this paper, we propose a primal-dual path following method for nonlinear semi-infinite semi-definite programs with infinitely many convex...
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An Interior Point-Proximal Method of Multipliers for Linear Positive Semi-Definite Programming
In this paper we generalize the Interior Point-Proximal Method of Multipliers (IP-PMM) presented in Pougkakiotis and Gondzio (Comput Optim Appl...
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Optimality Conditions for Nonlinear Second-Order Cone Programming and Symmetric Cone Programming
Nonlinear symmetric cone programming (NSCP) generalizes important optimization problems such as nonlinear programming, nonlinear semi-definite...
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Approximation of the Shannon Capacity Via Matrix Cone Programming
This paper proposes a novel formulation using the matrix cone programming to compute an upper bound of the Shannon capacity of graphs, which is...
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Calculating Radius of Robust Feasibility of Uncertain Linear Conic Programs via Semi-definite Programs
The radius of robust feasibility provides a numerical value for the largest possible uncertainty set that guarantees robust feasibility of an...
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Optimality Conditions in DC-Constrained Mathematical Programming Problems
This paper provides necessary and sufficient optimality conditions for abstract-constrained mathematical programming problems in locally convex...
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Solving Multi Objective Programming Problems Using Target Setting in DEA
Data Envelopment Analysis and Multiobjective Programming have many similarities. There are works which use MOLP methods to solve DEA problems in the...
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Dissipativity in Infinite Horizon Optimal Control and Dynamic Programming
In this paper we extend dynamic programming techniques to the study of discrete-time infinite horizon optimal control problems on compact control...
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IPRSDP: a primal-dual interior-point relaxation algorithm for semidefinite programming
We propose an efficient primal-dual interior-point relaxation algorithm based on a smoothing barrier augmented Lagrangian, called IPRSDP, for solving...
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Linear convergence rate analysis of proximal generalized ADMM for convex composite programming
The proximal generalized alternating direction method of multipliers (p-GADMM) is substantially efficient for solving convex composite programming...
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Optimization of the Optimal Value Function in Problems of Convex Parametric Programming
We consider a problem of convex parametric programming in which the objective function and the constraint functions are convex functions of an...
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Efficiency conditions and duality for multiobjective semi-infinite programming problems on Hadamard manifolds
This paper is devoted to the study of a class of multiobjective semi-infinite programming problems on Hadamard manifolds (in short, (MOSIP-HM)). We...
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Exact Vertex Migration Model of Graph Partitioning Based on Mixed 0–1 Linear Programming and Iteration Algorithm
Graph partitioning problem is a classical NP-hard problem. The improvement of graph partitioning results by vertex migration is an important class of...
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Constraint Qualifications and Optimality Criteria for Nonsmooth Multiobjective Programming Problems on Hadamard Manifolds
This article deals with a class of constrained nonsmooth multiobjective programming problems (NMOPP) in the setting of Hadamard manifolds. The...
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Self-adaptive algorithms for quasiconvex programming and applications to machine learning
For solving a broad class of nonconvex programming problems on an unbounded constraint set, we provide a self-adaptive step-size strategy that does...
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On proximal augmented Lagrangian based decomposition methods for dual block-angular convex composite programming problems
We design inexact proximal augmented Lagrangian based decomposition methods for convex composite programming problems with dual block-angular...
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Open issues and recent advances in DC programming and DCA
DC (difference of convex functions) programming and DC algorithm (DCA) are powerful tools for nonsmooth nonconvex optimization. This field was...
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Second-order cone and semidefinite methods for the bisymmetric matrix approximation problem
Approximating the closest positive semi-definite bisymmetric matrix using the Frobenius norm to a data matrix is important in many engineering...
