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首页> 外文期刊>Journal of Optimization Theory and Applications >Optimization for the Sum of Finite Functions Over the Solution Set of Split Equality Optimization Problems with Applications
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Optimization for the Sum of Finite Functions Over the Solution Set of Split Equality Optimization Problems with Applications

机译:应用程序解决方案集的有限功能总和

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摘要

In this paper, we adopt an iterative approach to solve the class of optimization problem for the sum of finite functions over split equality optimization problems for the sum of two functions. This type of problem contains many optimization problems, and bilevel problems, as well as split equality problems, and split feasibility problems as special cases. Here, we are able to establish a strong convergence theorem for an iterative method for solving this problem. As consequences of this convergence theorem, we study the following problems: optimization for the sum of finite functions over the common solution set of optimization problems for the sum of two functions; optimization for the sum of finite functions; optimization for the sum of finite functions with split equality inconsistent feasibility constraints; optimization for the sum of finite functions over the solution set for split equality constrained quadratic signal recovery problem; optimization for the sum of finite functions over the solution set of generalized split equality multiple set feasibility problem, and optimization for the sum of finite functions over the solution set of split equality linear equations problem. We use simultaneous iteration to establish strong convergence theorems for these problems. Our results generalize and improve many existing theorems for these types of problems in the literature and will have applications in nonlinear analysis, optimization problems and signal processing problems.
机译:在本文中,我们采用了一种迭代方法来解决优化问题,以便在两个函数的总和中分离平等优化问题的有限功能的总和。这种类型的问题包含许多优化问题,以及Bilevel问题,以及分裂平等问题,以及分割可行性问题作为特殊情况。在这里,我们能够为解决这个问题的迭代方法建立强大的收敛定理。作为这种融合定理的后果,我们研究了以下问题:优化用于在两个功能的总和中的常见解决方案集的有限功能的总和;优化用于有限功能的总和;具有分割平等不一致可行性约束的有限功能的优化;在解决方案集中的有限功能总和的优化,用于分离平等约束的二次信号恢复问题;通过解决方案集的有限功能总和优化,通过解决方案集的多个设置可行性问题,以及在分离平等线性方程问题的解决方案组中有限功能的优化。我们使用同时​​迭代来建立这些问题的强烈收敛定理。我们的成果概括和改善了这些类型存在于文献中的现有定理,并将在非线性分析,优化问题和信号处理问题中具有应用。

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