Search

In this study, we implement a variant of infeasible interior-point algorithm for solving monotone linear complementarity problems (LCP). We first reformulate the monotone LCP as an minimization problem. Then a descent iterative method is applied to the latter. The descent direction is computed via the Newton method. However, for maintaining the positivity of iterates, a novel and efficient strategy is proposed. Some numerical results are reported to show the efficiency of our proposed approach.

In this paper, we propose a large-update primal-dual interior point algorithm for convex quadratic semidefiniteoptimization (CQSDO) based on a new parametric kernel function. This kernel function is a parameterized version of the kernel function introduced by M.W. Zhang (Acta Mathematica Sinica. 28: 2313-2328, 2012) for CQSDO. The investigation according to it generating the best known iteration bound O for large-update methods. Thus improves the iteration bound obtained by Zhang for large-update methods. Finally, we present few numerical results to show the efficiency of the proposed algorithm.

In this paper a new weighted short-step primal-dual interior point algorithm to solve convex quadratic optimization (CQO) problems. The algorithm uses at each interior iteration afull-Newton step and the strategy of the central to obtain an epsilon-optimal solution of CQO. The algorithm yields the best currently best known theoretical complexity bound namely O(\sqrt(n) log n/epsilon).

In this paper we describe the preparation of a new aluminophosphate (AlPO-DACH) [C6 H18 N2Al4P5.32O21.32] by hydrothermal method. The structure was characterized by the single-crystal X ray diffraction. This material crystallizes in the trigonal system, space group P-3c1, a = 12.948 Å, b = 12.948 Å, c = 18.466 Å; α = 90° ; β = 90° ; γ = 120°.V = 26811(16)Å3, Z = 12, R:0.086 with 808 reflections. MATERIALS LETTERS, ISSN : 0167-577X, DOI: 10.1016/j.matlet.2011.04.047, Issue : 14, Volume : 65, pp. 2178 –2181, 31 JUILLET 2011.