共查询到20条相似文献,搜索用时 185 毫秒
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本文旨在针对线性比式和规划这一NP-Hard非线性规划问题提出新的全局优化算法.首先,通过引入p个辅助变量把原问题等价的转化为一个非线性规划问题,这个非线性规划问题的目标函数是乘积和的形式并给原问题增加了p个新的非线性约束,再通过构造凸凹包络的技巧对等价问题的目标函数和约束条件进行相应的线性放缩,构成等价问题的一个下界线性松弛规划问题,从而提出了一个求解原问题的分支定界算法,并证明了算法的收敛性.最后,通过数值结果比较表明所提出的算法是可行有效的. 相似文献
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本文研究了一类带有广义多项式约束的广义分式规划问题.首先将原问题转化为其等价形式,然后利用特殊不等式的有关性质将等价问题转化为易于求解的几何规划问题(GP),并通过求解一系列(GP)问题获得原问题的最优解.最后,给出求解问题的迭代算法以及算法的收敛性分析,数值算例表明提出的算法是可行有效的. 相似文献
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针对一般线性比式和问题的求解,给出一个新的分支定界算法.首先利用等价转换技巧和一个新的线性化技巧,建立等价问题的松弛线性化问题,将原始的非凸规划问题归结为一系列线性规划问题的求解;然后借助于这一系列松弛线性化问题的解确定出原问题的最优解.算法的收敛性理论上得以证明,数值算例表明算法是可行的. 相似文献
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带投资约束且p不确定的推广p-中位问题 总被引:1,自引:0,他引:1
p-中位问题是设施选址中的一个经典模型,在交通、物流等领域有着广泛应用.在经典p-中位问题的基础上提出一种p不确定的推广p-中位问题,并且加上总投资约束,使得此推广模型更加实用.针对此推广模型,提出三种启发式算法:简单启发式算法、变邻域搜索算法和改进的遗传算法.数值实验结果表明变邻域搜索算法和改进的遗传算法在求解此推广模型时是有效的. 相似文献
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Guoliang Xue 《Numerical Algorithms》1995,9(1):1-12
In this paper we partially resolve an open problem in spherical facility location. The spherical facility location problem is a generalization of the planar Euclidean facility location problem. This problem was first studied by Katz and Cooper and by Drezner and Wesolowsky where a Weszfeld-like algorithm was proposed. This algorithm is very simple and does not require a line search. However, its convergence has been an open problem for more than ten years. In this paper, we prove that the sequence generated by the algorithm converges to the unique optimal solution under the condition that the oscillation of the sequence converges to zero. We conjecture that the algorithm is a descent algorithm and prove that the sequence generated by the algorithm converges to the optimal solution under this conjecture. 相似文献
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Yair Censor,Aviv Gibali和Simeon Reich为求解变分不等式问题提出了2-次梯度外梯度算法。关于此算法的收敛性,作者给出了部分证明,有一个问题:由算法产生的迭代点列能否收敛到变分不等式问题的一个解上,没有得到解决。此问题作为一个公开问题在文章“Extensions of Korpelevich's extragradient method for the variational inequalityproblem in Euclidean space”(Optimization,61(9):1119-1132,2012)中被提出。在这篇简短的补注性文章中,对所提出的问题给出了答案:由算法产生的迭代点列能收敛到变分不等式问题的一个解上。给出2-次梯度外梯度算法的全局收敛性的一个完整证明,证明了从任意起始点开始,由算法产生的迭代点列都能收敛到变分不等式问题的一个解上。 相似文献
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This article presents a simplicial branch and bound algorithm for globally solving generalized linear multiplicative programming problem (GLMP). Since this problem does not seem to have been studied previously, the algorithm is apparently the first algorithm to be proposed for solving such problem. In this algorithm, a well known simplicial subdivision is used in the branching procedure and the bound estimation is performed by solving certain linear programs. Convergence of this algorithm is established, and some experiments are reported to show the feasibility of the proposed algorithm. 相似文献
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István Borgulya 《Central European Journal of Operations Research》2008,16(4):331-343
In this paper, we present a multi-objective evolutionary algorithm for the capacitated vehicle routing problem with route
balancing. The algorithm is based on a formerly developed multi-objective algorithm using an explicit collective memory method,
namely the extended virtual loser (EVL). We adapted and improved the algorithm and the EVL method for this problem. We achieved
good results with this simple technique. In case of this problem the quality of the results of the algorithm is similar to
that of other evolutionary algorithms. 相似文献
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求解log—最优组合投资问题的一个自适应算法及其理论分析 总被引:2,自引:0,他引:2
本文给出了一个求解log-最优组合投资问题的自适应算法,它是一个变型的随机逼近方法。该问题是一个约束优化问题,因此,采用基于约束流形的梯度上升方向替代常规梯度上升方向,在一些合理的假设下证明了算法的收敛性并进行了渐近稳定性分析。最后,本文将该算法应用于上海证券交易所提供的实际数据的log-最优组合投资问题求解,获得了理想的数值模拟结果。 相似文献
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A common problem frequently faced by business firms and individual investors is to select a few investment opportunities from many available possibilities. This problem, in its simplest form, can be modeled as a 0–1 knapsack problem. In a more general investment scenario, however, we obtain a model which is a general knapsack problem with a multiple-choice constraint. To solve this problem, an efficient enumerative algorithm is developed. The algorithm includes an efficient procedure to solve the LP-relaxed problem, a reduction algorithm which may allow the initial fixing of some of the variables, and various other implicit enumeration criteria derived from the group problem. Extensive computational experience illustrates the efficiency of the algorithm and related results. 相似文献
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Decomposition Branch-and-Bound Based Algorithm for Linear Programs with Additional Multiplicative Constraints 总被引:2,自引:0,他引:2
H. P. Benson 《Journal of Optimization Theory and Applications》2005,126(1):41-61
This article presents an algorithm for globally solving a linear program (P) that contains several additional multiterm multiplicative constraints. To our knowledge, this is the first algorithm proposed to date for globally solving Problem (P). The algorithm decomposes the problem to obtain a master problem of low rank. To solve the master problem, the algorithm uses a branch-and-bound scheme where Lagrange duality theory is used to obtain the lower bounds. As a result, the lower-bounding subproblems in the algorithm are ordinary linear programs. Convergence of the algorithm is shown and a solved sample problem is given. 相似文献
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In this paper, we consider an optimization problem which aims to minimize a convex function over the weakly efficient set of a multiobjective programming problem. To solve such a problem, we propose an inner approximation algorithm, in which two kinds of convex subproblems are solved successively. These convex subproblems are fairly easy to solve and therefore the proposed algorithm is practically useful. The algorithm always terminates after finitely many iterations by compromising the weak efficiency to a multiobjective programming problem. Moreover, for a subproblem which is solved at each iteration of the algorithm, we suggest a procedure for eliminating redundant constraints. 相似文献