仿射流形的双层析取优化

C. Udrişte, H. Bonnel, I. Ţevy, Ali SapeehRasheed
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引用次数: 2

摘要

双层优化是一种特殊的优化,其中一个问题嵌入到另一个问题中。外部优化任务通常称为上层优化任务,内部优化任务通常称为下层优化任务。这些问题涉及两类变量:上层变量和下层变量。双层优化首先在博弈论领域被德国经济学家冯·斯塔克尔伯格(von Stackelberg)实现,他在1934年出版了一本书,描述了这个层次问题。现在,双层优化问题在许多现实世界的问题中都很常见:交通运输、经济学、决策科学、商业、工程等等。在这一章中,我们提供了仿射流形上双层析取优化问题的一般公式。这些问题包含两个级别的优化任务,其中一个优化任务嵌套在另一个优化任务中。外部优化问题通常被称为领导者(上层)优化问题,内部优化问题被称为追随者(或下层)优化问题。这两个层面都有各自的目标和制约因素。主题:仿射凸函数,自动并行约束优化,拟多项式函数的仿射凸性,双层析取问题和算法,双层析取规划问题的模型,最小函数的性质。
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Bilevel Disjunctive Optimization on Affine Manifolds
Bilevel optimization is a special kind of optimization where one problem is embedded within another. The outer optimization task is commonly referred to as the upper-level optimization task, and the inner optimization task is commonly referred to as the lowerlevel optimization task. These problems involve two kinds of variables: upper-level variables and lower-level variables. Bilevel optimization was first realized in the field of game theory by a German economist von Stackelberg who published a book (1934) that described this hierarchical problem. Now the bilevel optimization problems are commonly found in a number of real-world problems: transportation, economics, decision science, business, engineering, and so on. In this chapter, we provide a general formulation for bilevel disjunctive optimization problem on affine manifolds. These problems contain two levels of optimization tasks where one optimization task is nested within the other. The outer optimization problem is commonly referred to as the leaders (upper level) optimization problem and the inner optimization problem is known as the followers (or lower level) optimization problem. The two levels have their own objectives and constraints. Topics affine convex functions, optimizations with auto-parallel restrictions, affine convexity of posynomial functions, bilevel disjunctive problem and algorithm, models of bilevel disjunctive programming problems, and properties of minimum functions.
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Bilevel Disjunctive Optimization on Affine Manifolds A Gradient Multiobjective Particle Swarm Optimization Piecewise Parallel Optimal Algorithm Multicriteria Support for Group Decision Making On Non-Linearity and Convergence in Non-Linear Least Squares
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