Scholarlink

<div class="x_elementToProof" data-ogsc="rgb(0, 0, 0)" data-olk-copy-source="MessageBody">Complementarity functions lie at the heart of modern optimization, offering a powerful way to reformulate the Karush-Kuhn-Tucker (KKT) conditions and the original optimization problem into more tractable forms, either as systems of equations or unconstrained minimization problems. These reformulations not only deepen theoretical understanding but also inspire innovative approaches for solving complex optimization challenges.</div><div class="x_elementToProof" data-ogsc="rgb(0, 0, 0)">&#xa0;</div><div class="x_elementToProof" data-ogsc="rgb(0, 0, 0)">This book centers on complementarity functions, offering a "big picture" view of their features and generating ideas for constructing new complementarity functions. The authors provide a comprehensive exploration of their key properties, structural features, and principles for constructing new complementarity functions while also demonstrating their value in algorithmic applications.</div><div class="x_elementToProof" data-ogsc="rgb(0, 0, 0)">&#xa0;</div><div class="x_elementToProof" data-ogsc="rgb(0, 0, 0)">This monograph carefully balances rigorous mathematical analysis with practical insight. It preserves the historical development of complementarity functions while guiding readers through their modern extensions and applications. It is an essential reference for graduate students, researchers, and practitioners in optimization, variational analysis, and applied mathematics.</div>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Complementarity Functions in Optimization

  • 书籍

  • 发表日期：

    2026年

查看全文
  • Jein-Shan Chen

摘要

Complementarity functions lie at the heart of modern optimization, offering a powerful way to reformulate the Karush-Kuhn-Tucker (KKT) conditions and the original optimization problem into more tractable forms, either as systems of equations or unconstrained minimization problems. These reformulations not only deepen theoretical understanding but also inspire innovative approaches for solving complex optimization challenges.
 
This book centers on complementarity functions, offering a "big picture" view of their features and generating ideas for constructing new complementarity functions. The authors provide a comprehensive exploration of their key properties, structural features, and principles for constructing new complementarity functions while also demonstrating their value in algorithmic applications.
 
This monograph carefully balances rigorous mathematical analysis with practical insight. It preserves the historical development of complementarity functions while guiding readers through their modern extensions and applications. It is an essential reference for graduate students, researchers, and practitioners in optimization, variational analysis, and applied mathematics.