A "joint+marginal" algorithm for polynomial optimization

Mathematics – Optimization and Control

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

We present a new algorithm for solving a polynomial program P based on the recent "joint + marginal" approach of the first author for, parametric optimization. The idea is to first consider the variable x1 as a parameter and solve the associated (n-1)-variable (x2,...,xn) problem P(x1) where the parameter x1 is fixed and takes values in some interval Y1 with some probability uniformly distributed on Y1. Then one considers the hierarchy of what we call "joint+marginal" semidefinite relaxations, whose duals provide a sequence of univariate polynomial approximations that converges to the optimal value function J(x1) of problem P(x1), as k increases. Then with k fixed a priori, one computes a minimizer of the univariate polynomial pk(x1) on the interval Y1, which reduces to solving a single semidefinite program. One iterates the procedure with now an (n-2)-variable problem P(x2) with parameter x2 in some new interval Y2, etc. The quality of the approximation depends on how large k can be chosen (in general for significant size problems, k=1 is the only choice). Preliminary numerical results are provided

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

A "joint+marginal" algorithm for polynomial optimization does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A "joint+marginal" algorithm for polynomial optimization, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A "joint+marginal" algorithm for polynomial optimization will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-556517

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.