Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Maryam Zangiabadi"'
Publikováno v:
Journal of Environmental Engineering and Landscape Management, Vol 26, Iss 2 (2018)
In recent years, inappropriate land use, urban and industrial development along with different pollutions emanating from it gives rise to loss of natural resources and further leads to destructive floods, soil erosion, sedimentation and other various
Externí odkaz:
https://doaj.org/article/36a14cc42dd645a9bc78a5230aab6c7b
Publikováno v:
Mathematical Modelling and Analysis, Vol 23, Iss 1 (2018)
An arc search interior-point algorithm for monotone symmetric cone linear complementarity problem is presented. The algorithm estimates the central path by an ellipse and follows an ellipsoidal approximation of the central path to reach an ε-approxi
Externí odkaz:
https://doaj.org/article/cbf3ff3a84b84586a1ccca912e54caa8
Publikováno v:
European Journal of Operational Research. 309:1316-1333
Publikováno v:
Afrika Matematika. 30:999-1009
Following the central-path, as a guide line to optimal solution of mathematical problems, is one of the main difficulty of interior-point methods in practice. These iterative methods, follow the central path step by step to get close enough to the op
Publikováno v:
Acta Mathematicae Applicatae Sinica, English Series. 35:359-373
In this paper, we present a neighborhood following primal-dual interior-point algorithm for solving symmetric cone convex quadratic programming problems, where the objective function is a convex quadratic function and the feasible set is the intersec
Publikováno v:
Optimization Methods and Software. 34:336-362
In this paper, we present a feasible predictor–corrector interior-point method for symmetric cone optimization problem in the large neighbourhood of the central path. The method is generalization of Ai-Zhang's predictor–corrector algorithm to the
Publikováno v:
Journal of Optimization Theory and Applications. 180:811-829
We present an infeasible interior-point predictor–corrector algorithm, based on a large neighborhood of the central path, for horizontal linear complementarity problem over the Cartesian product of symmetric cones. Throughout the paper, we assume t
Publikováno v:
Journal of the Operations Research Society of China. 8:145-164
In this paper, we propose an interior-point algorithm based on a wide neighborhood for convex quadratic semidefinite optimization problems. Using the Nesterov–Todd direction as the search direction, we prove the convergence analysis and obtain the
Publikováno v:
Optimization. 67:2031-2060
In this paper, we present a feasible interior-point algorithm for Cartesian horizontal linear complementarity problems in a new large neighbourhood of the central path. The new large neighbourhood is based on the infinity norm, and it is wider than t
Publikováno v:
Acta Mathematica Scientia. 38:1269-1284
In this paper, a corrector-predictor interior-point algorithm is proposed for symmetric optimization. The algorithm approximates the central path by an ellipse, follows the ellipsoidal approximation of the central-path step by step and generates a se