Evolutionary Global Optimization, Manifolds and Applications
暫譯: 進化全球最佳化、流形與應用
Aguiar E. Oliveira Junior, Hime
- 出版商: Springer
- 出版日期: 2019-03-30
- 售價: $4,510
- 貴賓價: 9.5 折 $4,285
- 語言: 英文
- 頁數: 137
- 裝訂: Quality Paper - also called trade paper
- ISBN: 3319799584
- ISBN-13: 9783319799582
海外代購書籍(需單獨結帳)
相關主題
商品描述
This book presents powerful techniques for solving global optimization problems on manifolds by means of evolutionary algorithms, and shows in practice how these techniques can be applied to solve real-world problems. It describes recent findings and well-known key facts in general and differential topology, revisiting them all in the context of application to current optimization problems. Special emphasis is put on game theory problems. Here, these problems are reformulated as constrained global optimization tasks and solved with the help of Fuzzy ASA. In addition, more abstract examples, including minimizations of well-known functions, are also included. Although the Fuzzy ASA approach has been chosen as the main optimizing paradigm, the book suggests that other metaheuristic methods could be used as well. Some of them are introduced, together with their advantages and disadvantages.
Readers should possess some knowledge of linear algebra, and of basic concepts of numerical analysis and probability theory. Many necessary definitions and fundamental results are provided, with the formal mathematical requirements limited to a minimum, while the focus is kept firmly on continuous problems. The book offers a valuable resource for students, researchers and practitioners. It is suitable for university courses on optimization and for self-study.
商品描述(中文翻譯)
這本書介紹了利用進化演算法解決流形上的全局優化問題的強大技術,並實際展示了這些技術如何應用於解決現實世界中的問題。書中描述了在一般和微分拓撲學中的最新發現和知名關鍵事實,並在當前優化問題的應用背景下重新審視這些內容。特別強調了博弈論問題。在這裡,這些問題被重新表述為受限的全局優化任務,並借助模糊自適應演算法(Fuzzy ASA)來解決。此外,還包括一些更抽象的例子,包括著名函數的最小化。雖然模糊自適應演算法被選為主要的優化範式,但本書建議也可以使用其他元啟發式方法。其中一些方法被介紹,並附上其優缺點。
讀者應具備一定的線性代數知識,以及數值分析和概率論的基本概念。書中提供了許多必要的定義和基本結果,並將正式的數學要求限制在最低限度,同時重點放在連續問題上。本書為學生、研究人員和實務工作者提供了寶貴的資源,適合用於大學的優化課程和自學。