Constrained global optimization of multivariate polynomials using polynomial B-spline form and B-spline consistency prune approach

In this paper, we propose basic and improved algorithms based on polynomial B-spline form for constrained global optimization of multivariate functions. The proposed are a branch-and-bound framework. algorithm introduce several new ingredients, such as box consistency hull to prune the search regions make more efficient. performance is tested compared set test problems. results tests show superiority over in terms chosen metrics 7 out-off 11 We compare optimal value minimum obtained using with CENSO, GloptiPoly state-of-the-art NLP solvers, CENSO solver (open source problem) that it always captures user-specified accuracy.