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71.
72.
Hadi Mohammadi Bidhandi 《Annals of Operations Research》2006,143(1):237-250
This paper develops a mathematical model for project time compression problems in CPM/PERT type networks. It is noted this
formulation of the problem will be an adequate approximation for solving the time compression problem with any continuous
and non-increasing time-cost curve. The kind of this model is Mixed Integer Linear Program (MILP) with zero-one variables,
and the Benders' decomposition procedure for analyzing this model has been developed. Then this paper proposes a new approach
based on the surrogating method for solving these problems. In addition, the required computer programs have been prepared
by the author to execute the algorithm. An illustrative example solved by the new algorithm, and two methods are compared
by several numerical examples. Computational experience with these data shows the superiority of the new approach. 相似文献
73.
The objective of this paper is to analyze under what well-known operations the class of quasipolyhedral convex functions,
which can be regarded as an extension of that of polyhedral convex functions, is closed. The operations that will be considered
are those that preserve polyhedral convexity, such that the image and the inverse image under linear transformations, right
scalar multiplication (including the case where λ=0+) and pointwise addition.
相似文献
74.
A. A. Maleev 《Computational Mathematics and Mathematical Physics》2006,46(12):2031-2039
Stationary and nonstationary Jacobi-like iterative processes for solving systems of linear algebraic equations are examined. For a system whose coefficient matrix A is an H-matrix, it is shown that the convergence rate of any Jacobi-like process is at least as high as that of the point Jacobi method as applied to a system with 〈A〉 as the coefficient matrix, where 〈A〉 is a comparison matrix of A. 相似文献
75.
关于矩阵条件数的一些结论 总被引:4,自引:1,他引:3
陈德辉 《华东师范大学学报(自然科学版)》1986,(3)
本文讨论了一些矩阵范数达到极小的充要条件,其主要结果如下:1.设?为m×n实矩阵,且具有n个线性无关的列,则求?广义逆谱条件数等于1的充要条件为?=cI,其中c为正常数.2.设?为n阶非异实矩阵,则矩阵A的求逆p-范数条件数等于1的充要条件为A=cpσ,其中c为正常数,σ是置换阵,其对角元都等于 1或-1.3.设?为n阶非异实矩阵,则矩阵4的求逆F-范数条件数等于1的充要条件为?=cU,其中c为正常数,U为正交阵. 相似文献
76.
77.
Patrizio Frosini 《Geometriae Dedicata》2004,108(1):105-110
In this paper we prove that for every real-valued Morse function φ on a smooth closed manifold ℳ and every neighborhood U of its critical points a suitable Riemannian metric μ
U
exists such that φ is linear outside
U 相似文献
78.
This paper develops a theory for the global solution of nonconvex optimization problems with parameter-embedded linear dynamic systems. A quite general problem formulation is introduced and a solution is shown to exists. A convexity theory for integrals is then developed to construct convex relaxations for utilization in a branch-and-bound framework to calculate a global minimum. Interval analysis is employed to generate bounds on the state variables implied by the bounds on the embedded parameters. These bounds, along with basic integration theory, are used to prove convergence of the branch-and-bound algorithm to the global minimum of the optimization problem. The implementation of the algorithm is then considered and several numerical case studies are examined thoroughly 相似文献
79.
80.
Some previous works show that symmetric fixed- and variable-stepsize linear multistep methods for second-order systems which do not have any parasitic root in their first characteristic polynomial give rise to a slow error growth with time when integrating reversible systems. In this paper, we give a technique to construct variable-stepsize symmetric methods from their fixed-stepsize counterparts, in such a way that the former have the same order as the latter. The order and symmetry of the integrators obtained is proved independently of the order of the underlying fixed-stepsize integrators. As this technique looks for efficiency, we concentrate on explicit linear multistep methods, which just make one function evaluation per step, and we offer some numerical comparisons with other one-step adaptive methods which also show a good long-term behaviour.