Sentence examples for multivariate optimization problem from inspiring English sources

As a consequence, CCO becomes a large scale non-separable multivariate optimization problem, where all cells must be jointly optimized.

Since we know both the ion image and the anatomical patterns and their relationship is established by the model, the search for the optimal anatomical contribution coefficients (and thus the optimal anatomical interpretation) can be approached as a multivariate optimization problem.

A curve is then modeled as a continuous, nonlinear and multivariate optimization problem with many local optima.

Several methods can be implemented to accomplish this multivariate optimization problem, such as a simplex method, Monte Carlo (MC) Sampling, [53] a genetic algorithm, nested sampling, [54] forward variable selection [31] or the conjugate gradient method [48].

The method of sequential updates corresponds to the coordinate descent method where multivariate optimization problem is solved by solving a sequence of scalar subproblems, each operating on a selected coordinate (scheduler) while all other coordinates are fixed.

By recognizing the polynomial nature of the phase mismatch, the design task is formulated as a nonconvex multivariate polynomial optimization problem, which is then solved through the latest convex programming techniques based on linear matrix inequality relaxations.

It belongs to the multivariate function optimization problems of nonlinear programming, and up to now it cannot use a mathematical expression to describe the relationship between the objective function and (K_{P}), (T_{I}), (T_{d}).

Artificial bee colony algorithm is an intelligent optimization algorithm proposed by Karaboga et al. [ 29– 31] to solve the multivariate function optimization problems based on the intelligent behavior of honey bee swarm.

This leads, however, to a very difficult multimodal and multivariate continuous nonlinear optimization problem, the so-called knot adjustment problem.

Because of its wide applicability, in this work we develop a multivariate investigation of this optimization problem.

These variables were accurately optimized using multivariate optimization strategies.