In a real situation, optimization problems often involve uncertain parameters. Robust optimization is one of distribution-free methodologies based on worst-case analyses for handling such problems. In this paper, we first focus on a special class of uncertain linear programs (LPs). Applying the...

Portfolio optimization problems involving value at risk (VaR) are often computationally intractable and require complete information about the return distribution of the portfolio constituents, which is rarely available in practice. These difficulties are compounded when the portfolio contains...

Convex underestimators of a polynomial on a box. Given a non convex polynomial <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$${f\in \mathbb{R}[{\rm x}]}$$</EquationSource> </InlineEquation> and a box <InlineEquation ID="IEq2"> <EquationSource Format="TEX">$${{\rm B}\subset \mathbb{R}^n}$$</EquationSource> </InlineEquation>, we construct a sequence of convex polynomials <InlineEquation ID="IEq3"> <EquationSource Format="TEX">$${(f_{dk})\subset \mathbb{R}[{\rm x}]}$$</EquationSource> </InlineEquation>, which converges in a strong sense to the...</equationsource></inlineequation></equationsource></inlineequation></equationsource></inlineequation>

The stable-set problem is an NP-hard problem that arises in numerous areas such as social networking, electrical engineering, environmental forest planning, bioinformatics clustering and prediction, and computational chemistry. While some relaxations provide high-quality bounds, they result in...

When using interior point methods for solving semidefinite programs (SDP), one needs to solve a system of linear equations at each iteration. For problems of large size, solving the system of linear equations can be very expensive. In this paper, we propose a trust region algorithm for solving...

The stable-set problem is an NP-hard problem that arises in numerous areas such as social networking, electrical engineering, environmental forest planning, bioinformatics clustering and prediction, and computational chemistry. While some relaxations provide high-quality bounds, they result in...

Extreme events occur rarely, but these are often the circumstances where an insurance coverage is demanded. Given the first, say, n moments of the risk(s) of the events, one is able to compute or approximate the tight bounds for risk measures in the form of E(ψ(x)) through semidefinite...