一本讲透优化算法原理与应用的实用指南，适合想深入理解优化技术的人。
Practical Topics in Optimization
- 从数学基础出发，结合直观解释推导核心优化方法
- 覆盖黑箱优化与随机优化等主流技术，强调适用场景判断
- 理论与实践平衡，适合学生、研究者和工程从业者
在数据驱动决策与计算效率至关重要的时代，优化在数学、计算机科学、运筹学、机器学习等领域发挥着基础性作用。从改进机器学习模型到优化资源配置与设计高效算法，优化技术是解决复杂问题的关键工具。本书旨在提供入门指导与全面参考，帮助读者掌握优化方法的理解与应用。核心目标是阐明优化算法（包括黑箱与随机优化器）的内在机制，通过形式化与直观解释相结合的方式，从基础数学原理出发推导关键结论，使读者不仅知其然，更知其所以然。通过理论深度与实际应用的精心平衡，本书面向广泛受众，包括学生、研究人员及寻求稳健优化策略的实践者。
原文摘要 · Abstract (English)
In an era where data-driven decision-making and computational efficiency are paramount, optimization plays a foundational role in advancing fields such as mathematics, computer science, operations research, machine learning, and beyond. From refining machine learning models to improving resource allocation and designing efficient algorithms, optimization techniques serve as essential tools for tackling complex problems. This book aims to provide both an introductory guide and a comprehensive reference, equipping readers with the necessary knowledge to understand and apply optimization methods within their respective fields. Our primary goal is to demystify the inner workings of optimization algorithms, including black-box and stochastic optimizers, by offering both formal and intuitive explanations. Starting from fundamental mathematical principles, we derive key results to ensure that readers not only learn how these techniques work but also understand when and why to apply them effectively. By striking a careful balance between theoretical depth and practical application, this book serves a broad audience, from students and researchers to practitioners seeking robust optimization strategies.
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