| 书目名称 | Stationarity and Convergence in Reduce-or-Retreat Minimization |
| 编辑 | Adam B. Levy |
| 视频video | |
| 概述 | Analyzes an innovative unifying framework for a wide variety of numerical methods? in optimization.Inspires new convergence analyses for existing methods in numerical optimization?.Extends and broaden |
| 丛书名称 | SpringerBriefs in Optimization |
| 图书封面 |  |
| 描述 | Stationarity and Convergence in Reduce-or-Retreat Minimization presents and analyzes a unifying framework for a wide variety of numerical methods in optimization. The author’s “reduce-or-retreat” framework is a conceptual method-outline that covers any method whose iterations choose between reducing the objective in some way at a trial point, or retreating to a closer set of trial points. The alignment of various derivative-based methods within the same framework encourages the construction of new methods, and inspires new theoretical developments as companions to results from across traditional divides. The text illustrates the former by developing two generalizations of classic derivative-based methods which accommodate non-smooth objectives, and the latter by analyzing these two methods in detail along with a pattern-search method and the famous Nelder-Mead method.In addition to providing a bridge for theory through the “reduce-or-retreat” framework, this monograph extends and broadens the traditional convergence analyses in several ways. Levy develops a generalized notion of approaching stationarity which applies to non-smooth objectives, and explores the roles of the des |
| 出版日期 | Book 2012 |
| 关键词 | convergence analysis; derivative-free methods; non-smooth analysis; numerical methods; reduce or retreat |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4614-4642-2 |
| isbn_softcover | 978-1-4614-4641-5 |
| isbn_ebook | 978-1-4614-4642-2Series ISSN 2190-8354 Series E-ISSN 2191-575X |
| issn_series | 2190-8354 |
| copyright | Adam B. Levy 2012 |
发表于 2025-3-21 17:58:44
