[PDF] Top 20 An Interval Matrix Based Generalized Newton Method for Linear Complementarity Problems

... penalized problems (1.2) corresponding to the linear complementarity problem ...that matrix A was symmetric positive ...the linear complementarity problem arising from pricing ... See full document

... modulus-based matrix splitting iterative methods [2, 6, 18, 19], see [9] for a survey of the iterative method for LCP ...the generalized AOR (GAOR) method [8, 12], which is a special ... See full document

... multigrid method with the PSOR method as smoother which runs efficiently on ...is based on matrix coloring and works well with sparse ...level-set method in image segmentation. Even ... See full document

... (local) linear convergence rate under certain conditions with O(np) per-iteration ...optimization method for computing the MLE is the Newton-Raphson method, which may be viewed as a reweighted ... See full document

... Generalized linear mixed models (GLMMs) are very useful for non-Gaussian correlated or clustered data and widely applied in many areas including epidemiology, ecological, and clinical ...approaches ... See full document

... cussions on the mapping F and its role in the study of the ICP (1.1), see [6]. By changing variables, Noor equivalently reformulated the ICP (1.1) as a fixed-point problem, which can be solved by some unified and general ... See full document

... stochastic linear complementarity ...stochastic linear complementarity problems into the equivalent fixed point equa- tions, then we establish a class of modulus-based ... See full document

... Our main goal is to analyse the convergence rates for projection methods under mild as- sumptions and together with strict contraction property, we establish convergence rates in asymptotical sense under certain error ... See full document

... stochastic generalized linear complementarity problems with finitely many elements is proposed for the first ...time. Based on the Fischer-Burmeister function, a new conjugate gradient ... See full document

... x ≤ Ax b − ≤ x Ax b − = (1.1) is called the linear complementarity problem (LCP). We call the problem the LCP (A, b). It is well known that several problems in optimization and engineering can be ... See full document

... smooth) Newton method is very efficient for some nonsmooth (or smooth) equations, which arise from the complementarity problem, the nonlinear programming problem, the variational inequality problem, ... See full document

... the matrix M for the LCP(M, q) belongs to P-matrices or some subclass of P- matrices, various bounds for () were proposed; ...a matrix M = [m ij ] ∈ R n,n is called ... See full document

... the generalized block pulse operational matrix,” Computers & Mathematics with Applications, ...equations based on the operational matrices of new fractional bernstein functions,” Journal of King ... See full document

... extended complementarity prob- lem, which eliminates the variable z in the ...problem, based on which we derive some new error bounds for the trans- formed problem and the original ... See full document

... of problems, as can be seen in the examples in chapter ...of interval analysis is inefficient and should be ...order interval extensions (Centered and Taylor Forms, Bernstein Forms, Taylor Models, ... See full document

... In this paper, new error bounds for the linear complementarity problem are obtained when the involved matrix is a weakly chained diagonally dominant B-matrix. The proposed error bounds are ... See full document

... the matrix M has always played a prominent role in the LCP theory since much depends on knowing the matrix through which the particular LCP is ...certain method are related to the matrix ... See full document

... Approximate Newton methods are standard optimization tools which aim to maintain the benefits of Newton’s method, such as a fast rate of convergence, while alleviating its drawbacks, such as computationally ... See full document

... world problems, the methodology for solving optimiza- tion problems has been ...optimization problems, namely deterministic optimization problem, stochastic optimization problem and ... See full document

... gradient projection method for MPCC is established. The smoothing factor µ regarded as a variable ensures that we can obtain an exact stationary point of original problem once the algorithm terminates in finite ... See full document