41 research outputs found
Minimizing Rational Functions by Exact Jacobian SDP Relaxation Applicable to Finite Singularities
This paper considers the optimization problem of minimizing a rational
function. We reformulate this problem as polynomial optimization by the
technique of homogenization. These two problems are shown to be equivalent
under some generic conditions. The exact Jacobian SDP relaxation method
proposed by Nie is used to solve the resulting polynomial optimization. We also
prove that the assumption of nonsingularity in Nie's method can be weakened as
the finiteness of singularities. Some numerical examples are given to
illustrate the efficiency of our method.Comment: 23 page
Semidefinite relaxations for semi-infinite polynomial programming
This paper studies how to solve semi-infinite polynomial programming (SIPP)
problems by semidefinite relaxation method. We first introduce two SDP
relaxation methods for solving polynomial optimization problems with finitely
many constraints. Then we propose an exchange algorithm with SDP relaxations to
solve SIPP problems with compact index set. At last, we extend the proposed
method to SIPP problems with noncompact index set via homogenization. Numerical
results show that the algorithm is efficient in practice.Comment: 23 pages, 4 figure
ECONOMIC-EMISSION DISPATCH WITH SEMIDEFINITE PROGRAMMING AND RATIONAL FUNCTION APPROXIMATIONS
The emission function associated with the economic-emission dispatch problem contains exponential functions that model the emission pollutants. This paper presents a strategy of solving the economic-emission dispatch problem whereby the exponential function is approximated by a rational function that permits reduction to a standard polynomial optimization problem. This is reformulated as a hierarchy of semidefinite relaxation problems using the moment theory and the resulting SDP problem is solved. Different degrees of rational functional approximation were considered. The approach was tested on the IEEE 30-bus test systems to investigate its effectiveness. Solutions obtained were compared with those from some of the well known evolutionary methods. Results showed that SDP has inherently good convergence property and a lower but comparable diversity property
Copositive certificates of non-negativity for polynomials on semialgebraic sets
A certificate of non-negativity is a way to write a given function so that
its non-negativity becomes evident. Certificates of non-negativity are
fundamental tools in optimization, and they underlie powerful algorithmic
techniques for various types of optimization problems. We propose certificates
of non-negativity of polynomials based on copositive polynomials. The
certificates we obtain are valid for generic semialgebraic sets and have a
fixed small degree, while commonly used sums-of-squares (SOS) certificates are
guaranteed to be valid only for compact semialgebraic sets and could have large
degree. Optimization over the cone of copositive polynomials is not tractable,
but this cone has been well studied. The main benefit of our copositive
certificates of non-negativity is their ability to translate results known
exclusively for copositive polynomials to more general semialgebraic sets. In
particular, we show how to use copositive polynomials to construct structured
(e.g., sparse) certificates of non-negativity, even for unstructured
semialgebraic sets. Last but not least, copositive certificates can be used to
obtain not only hierarchies of tractable lower bounds, but also hierarchies of
tractable upper bounds for polynomial optimization problems.Comment: 27 pages, 1 figur
Real Algebraic Geometry With A View Toward Systems Control and Free Positivity
New interactions between real algebraic geometry, convex optimization and free non-commutative geometry have recently emerged, and have been the subject of numerous international meetings. The aim of the workshop was to bring together experts, as well as young researchers, to investigate current key questions at the interface of these fields, and to explore emerging interdisciplinary applications
International Conference on Continuous Optimization (ICCOPT) 2019 Conference Book
The Sixth International Conference on Continuous Optimization took place on the campus of the Technical University of Berlin, August 3-8, 2019. The ICCOPT is a flagship conference of the Mathematical Optimization Society (MOS), organized every three years. ICCOPT 2019 was hosted by the Weierstrass Institute for Applied Analysis and Stochastics (WIAS) Berlin. It included a Summer School and a Conference with a series of plenary and semi-plenary talks, organized and contributed sessions, and poster sessions.
This book comprises the full conference program. It contains, in particular, the scientific program in survey style as well as with all details, and information on the social program, the venue, special meetings, and more