共查询到20条相似文献,搜索用时 146 毫秒
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用向量组共轭化方法改进Powell法 总被引:1,自引:0,他引:1
本文利用共轭化变换提高向量组共轭度的方法,对Powell法及修正Powell法作了改进。这一改进保持了原算法的二次终止性和关于连续可微严格凸函数的收敛性。文末用十六个公认的考机题检验了这一改进的效果。计算表明,改进后的Powell法及修正的Powell法比原算法收敛得快。 相似文献
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本文对Hilbert空间中关于非扩张映射不动点问题的粘滞逼近法提出一个修正,该修正后的算法取消了粘滞逼近法中的一个控制条件,并建立了该算法的一个强收敛定理. 相似文献
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修正Hestenes-Stiefel共轭梯度算法 总被引:4,自引:0,他引:4
本文探讨了Hestenes-Stiefel(HS)共轭梯度算法的收敛性条件.在无充分下降性条件下,证明了一种修正的HS共轭梯度算法的整体收敛性. 相似文献
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提出了半定规划(SDP)的一种修正的原对偶内点算法,对初始点的选取进行了改进,提高了算法的计算效率,并证明了新算法的迭代复杂性是O(n). 相似文献
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一类非单调修正PRP算法的全局收敛性 总被引:1,自引:0,他引:1
本文给出一类非单调线性搜索下的修正PRP算法,该方法保证每次迭代中的搜索方向是充分下降的.在较弱的条件下,我们证明了此类非单调修正PRP算法具有全局收敛性. 相似文献
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Li-Ping Pang Zun-Quan Xia Li-Wei Zhang 《Journal of Applied Mathematics and Computing》2003,11(1-2):201-213
In this paper we present a second order PVT (parallel variable transformation) algorithm converging to second order stationary points for minimizing smooth functions, based on the first order PVT algorithm due to Fukushima (1998). The corresponding stopping criterion, descent condition and descent step for the second order PVT algorithm are given. 相似文献
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Testing Parallel Variable Transformation 总被引:2,自引:0,他引:2
This paper studies performance of the parallel variable transformation (PVT) algorithm for unconstrained nonlinear optimization through numerical experiments on a Fujitsu VPP500, one of the most up-to-date vector parallel computers. Special attention is paid to a particular form of the PVT algorithm that is regarded as a generalization of the block Jacobi algorithm that allows overlapping of variables among processors. Implementation strategies on the VPP500 are described in detail and results of numerical experiments are reported. 相似文献
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In this paper, we modify a Multi-Objective Evolutionary Algorithm, known as Nondominated sorting Genetic Algorithm-II (NSGA-II) for a parallel machine scheduling problem with three objectives. The objectives are – (1) minimization of total cost due tardiness, (2) minimization of the deterioration cost and (3) minimization of makespan. The formulated problem has been solved by three Multi-Objective Evolutionary Algorithms which are: (1) the original NSGA-II (Non-dominated Sorting Genetic Algorithm–II), (2) SPEA2 (Strength Pareto Evolutionary Algorithm-2) and (3) a modified version of NSGA-II as proposed in this paper. A new mutation algorithm has also been proposed depending on the type of problem and embedded in the modified NSGA-II. The results of the three algorithms have been compared and conclusions have been drawn. The modified NSGA-II is observed to perform better than the original NSGA-II. Besides, the proposed mutation algorithm also works effectively, as evident from the experimental results. 相似文献
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As a synchronization parallel framework, the parallel variable transformation (PVT) algorithm is effective to solve unconstrained optimization problems. In this paper, based on the idea that a constrained optimization problem is equivalent to a differentiable unconstrained optimization problem by introducing the Fischer Function, we propose an asynchronous PVT algorithm for solving large-scale linearly constrained convex minimization problems. This new algorithm can terminate when some processor satisfies terminal condition without waiting for other processors. Meanwhile, it can enhances practical efficiency for large-scale optimization problem. Global convergence of the new algorithm is established under suitable assumptions. And in particular, the linear rate of convergence does not depend on the number of processors. 相似文献
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On the superlinear local convergence of a filter-SQP method 总被引:5,自引:0,他引:5
Transition to superlinear local convergence is shown for a modified version of the trust-region filter-SQP method for nonlinear programming introduced by Fletcher, Leyffer, and Toint [8]. Hereby, the original trust-region SQP-steps can be used without an additional second order correction. The main modification consists in using the Lagrangian function value instead of the objective function value in the filter together with an appropriate infeasibility measure. Moreover, it is shown that the modified trust-region filter-SQP method has the same global convergence properties as the original algorithm in [8].Mathematics Subject Classification (2000): 90C55, 65K05, 90C30 相似文献
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A parallel stochastic algorithm is presented for solving the linearly constrained concave global minimization problem. The algorithm is a multistart method and makes use of a Bayesian stopping rule to identify the global minimum with high probability. Computational results are presented for more than 200 problems on a Cray X-MP EA/464 supercomputer. 相似文献
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Parallel Implementation of Synchronous Type Artificial Bee Colony Algorithm for Global Optimization 总被引:1,自引:0,他引:1
Evolutionary algorithms often need huge running times when solving large-scale optimization problems. One of the solutions for this issue is to introduce parallelization into the algorithm. To benefit from this approach for the artificial bee colony optimization algorithm, we present a new synchronous and parallel version of the algorithm. Performances of the proposed version and the original asynchronous algorithm are compared in terms of efficiency and speedup. Algorithms are competed to solve 20 large-scale global optimization problems. Comparative results show that the proposed parallel algorithm is still efficient as asynchronous version while it requires much less time to solve complex and large problems. 相似文献
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C.A.J. HurkensT. Vredeveld 《Operations Research Letters》2003,31(2):137-141
We analyze two local search algorithms for multiprocessor scheduling. The first algorithm is a job interchange algorithm for identical parallel machines due to Finn and Horowitz (Bit 19 (1979) 312). We construct instances for which this algorithm takes a quadratic number of iterations. This contradicts the original analysis of Finn and Horowitz who claimed a linear number of iterations.The second algorithm adds an additional rule to the Finn and Horowitz algorithm. Even for n jobs on m uniformly related machines, this modified algorithm takes only O(nm) iterations. 相似文献
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M. I. Sumin 《Computational Mathematics and Mathematical Physics》2007,47(5):760-779
For a nonlinear programming problem with equality constraints in a Hilbert space, a dual-type algorithm is constructed that is stable with respect to input data errors. The algorithm is based on a modified dual of the original problem that is solved directly by applying Tikhonov regularization. The algorithm is designed to determine a norm-bounded minimizing sequence of feasible elements. An iterative regularization of the dual algorithm is considered. A stopping rule for the iteration process is given in the case of a finite fixed error in the input data. 相似文献