基于核函数的线性分数问题原始双内点法的扩展

Mousaab Bouafia, Adnan Yassine
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摘要

我们在这项工作中的目标是扩展基于核函数的初等二元内点法,以解决线性分数问题。我们将基于核函数的内点法技术应用于求解标准线性分数程序。依靠 Charnes 和 Cooper [3] 的方法,我们将标准线性分数问题转化为线性程序。通过这种转换,我们可以定义相关的线性程序,并使用适当的核函数高效地求解。为了展示我们方法的效率,我们将算法应用于 A. Bennani 等人的论文[4]中数值测试发现的标准线性分数程序,并介绍了与该问题相关的线性程序。我们给出了与问题维度相关的三个内点条件。我们给出了每个线性规划和每个线性分数规划的最优解。我们还利用新算法得到了前两个问题的最优解。此外,我们还通过一些数值结果来说明该方法的有效性。
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Extension of primal-dual interior point method based on a kernel function for linear fractional problem
Our aim in this work is to extend the primal-dual interior point method based on a kernel function for linear fractional problem. We apply the techniques of kernel function-based interior point methods to solve a standard linear fractional program. By relying on the method of Charnes and Cooper [3], we transform the standard linear fractional problem into a linear program. This transformation will allow us to define the associated linear program and solve it efficiently using an appropriate kernel function. To show the efficiency of our approach, we apply our algorithm on the standard linear fractional programming found in numerical tests in the paper of A. Bennani et al. [4], we introduce the linear programming associated with this problem. We give three interior point conditions on this example, which depend on the dimension of the problem. We give the optimal solution for each linear program and each linear fractional program. We also obtain, using the new algorithm, the optimal solutions for the previous two problems. Moreover, some numerical results are illustrated to show the effectiveness of the method.
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Adaptation of the composite finite element framework for semilinear parabolic problems A comparative study of Filon-type rules for oscillatory integrals Local convergence analysis of frozen Steffensen-type methods under generalized conditions Extension of primal-dual interior point method based on a kernel function for linear fractional problem Nonlinear random extrapolation estimates of \(\pi\) under Dirichlet distributions
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