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一种修正的求约束总极值的积分-水平集方法 总被引:3,自引:0,他引:3
对于有约束的全局最优化问题,在Chew-Zheng的《Integral Global Optimization》和邬冬华等的《一种修正的求总极值的积分-水平集方法的实现算法收敛性》的基础上,给出一种修正的求约束总极值的积分-水平集方法,它同样具有修正的求总极值的积分-水平集方法的两个特点: 1) 每一步构造一个新函数,它与原目标函数具有相同的总极值; 2) 避免了郑权算法在一般情况下,由于水平集不易求得而造成难以求出水平集的困难.同时给出了其实现算法,并证明了算法的收敛性. 相似文献
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本文考虑有约束的非线性互补问题的全局最优化问题,在文《IntegralGlobalOptimizationMethodforSolutionofNonlinearComplementarityproblem》和《一种修正的求总极值的积分一水平集方法》的基础上,给出了一种修正的求约束总极值的积分一水平集方法,它同样具有修正的求总极值的积分一水平集方法的两个特点:1)每一步需要构造一个新的函数,而且它与原目标函数具有相同的总极值;2)避免了郑权算法在一般情况下,由于水平集不易求得而造成难以求出水平的困难,并证明了算法的收敛性 相似文献
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本文考虑有约束的非线性互补问题的全局最优化问题,在文《Integral Global Optimization Method fro Solution of Nonlinear Complementarity problem》和《一的求总极值的积分-水平集方法》的基础上,给出了一种修正的求约束总极值的积分-水平集方法,它同样具有修正的求总极值的积分-水平集方法的两个特点:1)第一步需要构造一个新的函数,而且它与原目标函数具有相同的总极值;2)避免了郑权算法在一般情况下,由于水平集不易求得而造成难以求出水平的困难,并证明了算法的收敛性。 相似文献
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多目标最优化的一种积分型实现算法 总被引:2,自引:1,他引:1
在文[1]中给出了求解多目标最优化的一种积分总极值的概念性算法.本文利用数论中的一致分布佳点集列,较为简便的得出了多目标最优化的积分总极值的实现算法和算法终止准则.并经过有关函数数值计算表明该算法是有效的,可用来求解多目标最优化问题的有效解. 相似文献
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积分—水平集总极值算法的另一实现途径 总被引:8,自引:1,他引:7
在(1)中提出了一个积分-水平集求总极值的概念性算法及Monte-Carlo随机投点的实现途径,并在不少实际问题中得到了很好的应用。但这一实际算法的收敛性是个未解决的问题。本文给出了另一实现途径,并证明了收敛性。从而从理论上证明了这一实现算法一定能求到总极值和总极值点,数值试验结果也支持这一理论结果。 相似文献
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一个求总极值的实现算法及其收敛性 总被引:7,自引:0,他引:7
1978年,郑权等首先提出了一种用积分─水平集求总极值的方法及用Monte-Carlo随机投点实现的实现其法,其实现算法是否收敛未解决的问题.本文提出一种用数论方法实现的实现算法,并证明了该实现其法是收敛的.初步的数值结果表明,该实现其法是较有效的. 相似文献
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Most parallel efficient global optimization (EGO) algorithms focus only on the parallel architectures for producing multiple updating points, but give few attention to the balance between the global search (i.e., sampling in different areas of the search space) and local search (i.e., sampling more intensely in one promising area of the search space) of the updating points. In this study, a novel approach is proposed to apply this idea to further accelerate the search of parallel EGO algorithms. In each cycle of the proposed algorithm, all local maxima of expected improvement (EI) function are identified by a multi-modal optimization algorithm. Then the local EI maxima with value greater than a threshold are selected and candidates are sampled around these selected EI maxima. The results of numerical experiments show that, although the proposed parallel EGO algorithm needs more evaluations to find the optimum compared to the standard EGO algorithm, it is able to reduce the optimization cycles. Moreover, the proposed parallel EGO algorithm gains better results in terms of both number of cycles and evaluations compared to a state-of-the-art parallel EGO algorithm over six test problems. 相似文献
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A Comparison of Global Optimization Methods for the Design of a High-speed Civil Transport 总被引:1,自引:0,他引:1
Steven E. Cox Raphael T. Haftka Chuck A. Baker Bernard Grossman William H. Mason Layne T. Watson 《Journal of Global Optimization》2001,21(4):415-432
The conceptual design of aircraft often entails a large number of nonlinear constraints that result in a nonconvex feasible design space and multiple local optima. The design of the high-speed civil transport (HSCT) is used as an example of a highly complex conceptual design with 26 design variables and 68 constraints. This paper compares three global optimization techniques on the HSCT problem and two test problems containing thousands of local optima and noise: multistart local optimizations using either sequential quadratic programming (SQP) as implemented in the design optimization tools (DOT) program or Snyman's dynamic search method, and a modified form of Jones' DIRECT global optimization algorithm. SQP is a local optimizer, while Snyman's algorithm is capable of moving through shallow local minima. The modified DIRECT algorithm is a global search method based on Lipschitzian optimization that locates small promising regions of design space and then uses a local optimizer to converge to the optimum. DOT and the dynamic search algorithms proved to be superior for finding a single optimum masked by noise of trigonometric form. The modified DIRECT algorithm was found to be better for locating the global optimum of functions with many widely separated true local optima. 相似文献
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提出了结合仿射尺度技术的正割算法解非线性等式与有界约束优化问题.
在合理假设下, 证明了渐弱滤子线搜索方法可以保证新算法具有整体收敛性.
通过引入一个高阶修正方向, 克服Maratos效应的影响, 使得算法二步$q$-\!\!超线性收敛于最优点.
进一步地, 对算法进行修改, 使得新算法达到$q$-\!\!超线性收敛性. 相似文献
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变测度的积分-水平集确定性算法 总被引:3,自引:0,他引:3
提出了一个求总极值的变测度确定性算法,对不同的箱子采用不同的测度,结合确定性数论方法选取一致分布佳点集来代替Monte-Carlo随机投点,使水平值充分地下降,更快地到达全局最小,从而提高算法的计算效率.在文中给出了算法的收敛性证明,并通过数值算例验证了它的有效性. 相似文献
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大洪水算法在平面选址问题中的应用 总被引:1,自引:0,他引:1
大洪水算法是通过模拟洪水上涨过程来进行全局寻优的启发式算法.针对连续优化问题,基于三种不同的邻域搜索策略对其进行改进,并针对一类平面选址问题进行应用测试.仿真结果表明,大洪水算法是一类简单高效的算法,可用于连续优化问题的求解. 相似文献
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Gonglin Yuan 《Numerical Functional Analysis & Optimization》2013,34(8):914-937
Mathematical programming is a rich and well-developed area in operations research. Nevertheless, there remain many challenging problems in this area, one of which is the large-scale optimization problem. In this article, a modified Hestenes and Stiefel (HS) conjugate gradient (CG) algorithm with a nonmonotone line search technique is presented. This algorithm possesses information about not only the gradient value but also the function value. Moreover, the sufficient descent condition holds without any line search. The global convergence is established for nonconvex functions under suitable conditions. Numerical results show that the proposed algorithm is advantageous to existing CG methods for large-scale optimization problems. 相似文献
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提出一类新的求解无约束优化问题的记忆梯度法,证明了算法的全局收敛性.当目标函数为一致凸函数时,对其线性收敛速率进行了分析.新算法在迭代过程中无需对步长进行线性搜索,仅需对算法中的一些参数进行预测估计,从而减少了目标函数及梯度的迭代次数,降低了算法的计算量和存储量.数值试验表明算法是有效的. 相似文献
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Chaotic bat algorithm 总被引:1,自引:0,他引:1
《Journal of computational science》2014,5(2):224-232
Bat algorithm (BA) is a recent metaheuristic optimization algorithm proposed by Yang. In the present study, we have introduced chaos into BA so as to increase its global search mobility for robust global optimization. Detailed studies have been carried out on benchmark problems with different chaotic maps. Here, four different variants of chaotic BA are introduced and thirteen different chaotic maps are utilized for validating each of these four variants. The results show that some variants of chaotic BAs can clearly outperform the standard BA for these benchmarks. 相似文献
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为了提高鲸鱼优化算法(WOA)的全局优化性能, 提出了一种基于黄金分割搜索的改进鲸鱼优化算法(GWOA)。首先利用黄金分割搜索对WOA的初始种群进行初始化, 使得初始种群能够尽可能的靠近全局最优解, 然后利用黄金分割搜索所形成的变区间, 进行变区间黄金分割非均匀变异操作, 以增加WOA的粒子多样性和提高粒子跳出局部最优陷阱的能力, 从而改善WOA的寻优性能。选取了15个大规模测试函数进行数值仿真测试, 仿真结果和统计分析表明GWOA的寻优性能要优于对比文献的改进鲸鱼优化算法(IWOA)。此外, 将GWOA用于对工程实际应用领域中的电力负荷优化调度问题进行实例分析, 实例应用结果表明, GWOA能有效对电力负荷优化调度问题进行寻优求解。 相似文献