Sentence examples for finding a solution of the minimization from inspiring English sources

Next, we introduce an explicit algorithm for finding a solution of the minimization problem (1.1).

In this section, we prove a strong convergence theorem by an iterative algorithm for finding a solution of the constrained convex minimization problem (1.4), which is also a common solution of the quasi-variational inclusion problem (1.1) and the fixed point problem of a k-strictly pseudo-contractive mapping (1.3) in a real Hilbert space.

The purpose of this paper is to introduce an iterative algorithm for finding a solution of quadratic minimization problem in the set of fixed points of a nonexpansive mapping and to prove a strong convergence theorem of the solution for quadratic minimization problem.

Using this result, we consider the convex minimization problem of finding a minimizer of a proper lower-semicontinuous convex function and the variational problem of finding a solution of a variational inequality.

In this paper we introduce a multi-step implicit iterative scheme with regularization for finding a common solution of the minimization problem (MP) for a convex and continuously Fréchet differentiable functional and the common fixed point problem of an infinite family of nonexpansive mappings in the setting of Hilbert spaces.

Therefore, x ∗ is a solution of the minimization problem (1.1).

Let x ∗ be a solution of the minimization problem (10).

Then { x n } n = 0 ∞ converges weakly to a solution of the minimization problem (1.1).

□ We do not assume a priori that a solution of the minimization problem (4) exists.

To cope with this difficulty, we propose that a penalty term be included in the objective function in each minimization to discourage the optimizer from finding a solution in the regions of state space where the local data density is inadequately low.

"Part of finding a solution is exposing the problem".