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借助于极大熵方法和逼近法,给出了一种求解约束极小极大问题的K-S函数近似迭代法,同时讨论算法的有关收敛性. 相似文献
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黄时祥 《数学的实践与认识》2007,37(5):83-88
利用极大熵方法将带多个非线性不等式约束和多个非线性等式约束的多目标规划问题变为两个非线性不等式约束的单个可微的目标函数优化问题,并结合区间分析知识给出一种新的解决多目标规划问题的区间方法. 相似文献
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求解约束极大极小问题的一种熵函数法 总被引:7,自引:0,他引:7
1引言熵函数法的原始思想源于Kreisselmeier和Steinhauser于1979年发表的文[1].由于使用该方法容易编制可以求解多类优化问题的通用软件,并在具有某种凸性的情况下都能求得满足工程精度要求的解,因而受到国内外工程技术人员的喜爱,进入八十年代以来,该方法被广泛地应用于结构优化和工程设计等领域[2-5].近年来,熵函数法在求解约束和无约束极大极小问题、线性规划以及半无限规划等问题的算法研究中,也取得了一些很好的成果[6-9]带有等式或不等式约束的极大极小问题是一类具有广泛代表性的… 相似文献
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本文通过利用极大熵函数构造同伦映射,建立了求解无约束线性l1模问题的熵函数延拓算法,证明了方法的收敛性,并给出了数值算例. 相似文献
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提出求解含平衡约束数学规划问题(简记为MPEC问题)的熵函数法,在将原问题等价改写为单层非光滑优化问题的基础上,通过熵函数逼近,给出求解MPEC问题的序列光滑优化方法,证明了熵函数逼近问题解的存在性和算法的全局收敛性,数值算例表明了算法的有效性。 相似文献
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多目标规划的一类基于精确罚函数的交互式方法 总被引:3,自引:0,他引:3
该文在约束集的线性化锥非空的条件下,得到了带有等式和不等式约束的多目标规划问题的精确罚函数的存在性,用原问题的二次近似在某些点上的Kuhn-Tucker乘子给出了罚因子的下界.在此基础上,利用极大熵方法的思想将罚问题转化为可微的无约束多目标规划问题并给出了求解该问题的一种交互式算法.数值结果表明:该文算法具有计算速度快、精度高、适用范围广且易于理解和使用等优点. 相似文献
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In order to solve the constrained global optimization problem,we use penalty functions not only on constraints but also on objective function. Then within the framework of interval analysis,an interval Branch-and-Bound algorithm is given,which does not need to solve a sequence of unconstrained problems. Global convergence is proved. Numerical examples show that this algorithm is efficient. 相似文献
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构造了求解一类带不等式约束的min-max-min问题的区间算法,其中目标函数和约束函数都是一阶连续可微函数,证明了方法的收敛性,给出了数值算例.该方法可以同时求出问题的最优值和全部全局最优解,是有效和可靠的. 相似文献
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Summary The problem of computing constrained spline functions, both for ideal data and noisy data, is considered. Two types of constriints are treated, namely convexity and convexity together with monotonity. A characterization result for constrained smoothing splines is derived. Based on this result a Newton-type algorithm is defined for computing the constrained spline function. Thereby it is possible to apply the constraints over a whole interval rather than at a discrete set of points. Results from numerical experiments are included. 相似文献
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本文给出了一类新的求解箱约束全局整数规划问题的填充函数,并讨论了其填充性质.基于提出的填充函数,设计了一个求解带等式约束、不等式约束、及箱约束的全局整数规划问题的算法.初步的数值试验结果表明提出的算法是可行的。 相似文献
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一类无约束离散Minimax问题的区间调节熵算法 总被引:3,自引:0,他引:3
LiSubei CaoDexin WangHaijun DengKazhong 《高校应用数学学报(英文版)》2004,19(1):37-43
In this paper,a class of unconstrained discrete minimax problems is described,in which the objective functions are in C^1. The paper deals with this problem by means of taking the place of maximum-entropy function with adjustable entropy function. By constructing an interval extension of adjustable entropy function and some region deletion test rules, a new interval algorithm is presented. The relevant properties are proven, The minimax value and the localization of the minimax points of the problem can be obtained by this method. This method can overcome the flow problem in the maximum-entropy algorithm. Both theoretical and numerical results show that the method is reliable and efficient. 相似文献
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Based on the maximum entropy principle and the idea of a penalty function, an evaluation function is derived to solve multiobjective optimization problems with equality constraints. Combining with interval analysis method, we define a generalized Krawczyk operator, design interval iteration with constrained functions and new region deletion test rules, present an interval algorithm for equality constrained multiobjective optimization problems, and also prove relevant properties. A theoretical analysis and numerical results indicate that the algorithm constructed is effective and reliable. 相似文献
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针对约束非线性l_1问题不可微的特点,提出了一种光滑近似算法.该方法利用" "函数的光滑近似函数和罚函数技术将非线性l_1问题转化为无约束可微问题,并在适当的假设下,该算法是全局收敛的.初步的数值试验表明算法的有效性. 相似文献
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This paper considers the nonlinearly constrained continuous global minimization problem. Based on the idea of the penalty function method, an auxiliary function, which has approximately the same global minimizers as the original problem, is constructed. An algorithm is developed to minimize the auxiliary function to find an approximate constrained global minimizer of the constrained global minimization problem. The algorithm can escape from the previously converged local minimizers, and can converge to an approximate global minimizer of the problem asymptotically with probability one. Numerical experiments show that it is better than some other well known recent methods for constrained global minimization problems. 相似文献