基于修正的指数函数的概率约束问题的对偶算法
A Dual Algorithm for Probabilistic Constraint Problems Based on Modified Exponential Functions
摘要: 本文通过连续可微的非凸函数所形成的概率约束，来分析概率约束问题。描述了潜在的概率函数的水平集的切锥和法锥。进一步，基于p-有效点的概念，形成这些问题的一阶和二阶最优性条件。对于离散分布函数的这种情况，产生一个基于修正的指数函数的对偶算法来解决概率约束问题。
Abstract: In this paper, the problem of probability constraints is analyzed by means of the probability constraints formed by continuously differentiable non-convex functions. The tangent and normal cones of the level set of potential probability functions are described. Further, based on the concept of p-efficient points, the first and second order optimality conditions of these problems are formed. For this case of the discrete distribution function, a dual algorithm based on the modified exponential function is generated to solve the probability constraint problem.
文章引用：张微, 张瑛珏, 王禹钧. 基于修正的指数函数的概率约束问题的对偶算法[J]. 应用数学进展, 2024, 13(11): 5025-5031. https://doi.org/10.12677/aam.2024.1311485

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