The optimal logical layout design for a type of machining transfer lines is addressed. Such transfer lines are made of many machine-tools (workstations) located in sequence. On each workstation there are several spindle-heads. A spindle-head does not execute a single operation but a block of machining operations simultaneously. Spindle-heads of the same workstation are activated sequentially in...

Abstract In this paper, we propose two hybrid inertial CQ projection algorithms with line-search process for the split feasibility problem. Based on algorithm, firstly add term into iteration to accelerate convergence of and adopt flexible rules selecting stepsize shrinking region, which makes an optimal available at each iteration. The region is intersection three sets, are set C hyperplanes. ...

It is generally acknowledged that the conjugate gradient (CG) method achieves global convergence--with at most a linear convergence rate--because CG formulas are generated by linear approximations of the objective functions. The quadratically convergent results are very limited. We introduce a new PRP method in which the restart strategy is also used. Moreover, the method we developed includes ...

Conjugate gradient methods are an important class of methods for solving unconstrained optimization problems, especially for large-scale problems. Recently, they have been studied in depth. In this paper, we further study the conjugate gradient method for unconstrained optimization. We focus our attention to the descent conjugate gradient method. This paper presents a modified conjugate gradien...

We investigate the behavior of quasi-Newton algorithms applied to minimize a nonsmooth function f , not necessarily convex. We introduce an inexact line search that generates a sequence of nested intervals containing a set of points of nonzero measure that satisfy the Armijo and Wolfe conditions if f is absolutely continuous along the line. Furthermore, the line search is guaranteed to terminat...

This paper proposes a general framework for implementing backtracking search strategies in Propositional Satisfiability (SAT) algorithms, that is referred to unrestricted backtracking. Different organizations of unrestricted backtracking yield well-known backtracking search strategies. Moreover, this general framework allows devising new backtracking strategies. Hence, we illustrate and compare...

This paper establishes finite active-set identification of an almost cyclic 2-coordinate descent method for problems with one linear coupling constraint and simple bounds. First, general results are stated nonconvex objective functions. Then, under convexity a quadratic growth condition (satisfied by any strongly convex function), complexity on the number iterations required to identify active ...

The nonlinear conjugate gradient (CG) algorithm is a very effective method for optimization, especially for large-scale problems, because of its low memory requirement and simplicity. Zhang et al. (IMA J. Numer. Anal. 26:629-649, 2006) firstly propose a three-term CG algorithm based on the well known Polak-Ribière-Polyak (PRP) formula for unconstrained optimization, where their method has the s...

<p style='text-indent:20px;'>This paper proposes a nonmonotone spectral gradient method for solving large-scale unconstrained optimization problems. The parameter is derived from the eigenvalues of an optimally sized memoryless symmetric rank-one matrix obtained under measure defined as ratio determinant updating over its largest eigenvalue. Coupled with line search strategy where backtra...