Nature-Inspired Optimization Algorithms (Paperback)

Nature-Inspired Optimization Algorithms, a comprehensive work on the most popular optimization algorithms based on nature, starts with an overview of optimization going from the classical to the latest swarm intelligence algorithm. Nature has a rich abundance of flora and fauna that inspired the development of optimization techniques, providing us with simple solutions to complex problems in an effective and adaptive manner. The study of the intelligent survival strategies of animals, birds, and insects in a hostile and ever-changing environment has led to the development of techniques emulating their behavior.

This book is a lucid description of fifteen important existing optimization algorithms based on swarm intelligence and superior in performance. It is a valuable resource for engineers, researchers, faculty, and students who are devising optimum solutions to any type of problem ranging from computer science to economics and covering diverse areas that require maximizing output and minimizing resources. This is the crux of all optimization algorithms.
Features:

• Detailed description of the algorithms along with pseudocode and flowchart
• Easy translation to program code that is also readily available in Mathworks website for some of the algorithms
• Simple examples demonstrating the optimization strategies are provided to enhance understanding
• Standard applications and benchmark datasets for testing and validating the algorithms are included

This book is a reference for undergraduate and post-graduate students. It will be useful to faculty members teaching optimization. It is also a comprehensive guide for researchers who are looking for optimizing resources in attaining the best solution to a problem. The nature-inspired optimization algorithms are unconventional, and this makes them more efficient than their traditional counterparts.

《自然啟發的優化演算法》是一本關於基於自然的最流行優化演算法的綜合性著作，從經典到最新的群體智能演算法，全面介紹了優化的概述。自然界擁有豐富的植物和動物資源，啟發了優化技術的發展，以有效且適應性的方式為複雜問題提供簡單的解決方案。對動物、鳥類和昆蟲在惡劣且不斷變化的環境中的智能生存策略的研究，促使了模仿它們行為的技術的發展。

本書詳細描述了基於群體智能的十五種重要優化演算法，並在性能上優越。對於工程師、研究人員、教師和學生來說，這是一個寶貴的資源，他們正在設計從計算機科學到經濟學等各種問題的最佳解決方案，並在需要最大化輸出和最小化資源的各個領域提供支持。這是所有優化演算法的核心。

特點：
- 詳細描述演算法，包括偽代碼和流程圖
- 易於轉換為程式碼，部分演算法的程式碼也可在Mathworks網站上輕鬆獲得
- 提供簡單的示例來展示優化策略，以增強理解
- 包含用於測試和驗證演算法的標準應用和基準數據集

本書是本科和研究生學生的參考書。對於教授優化課程的教師來說，它也是一本全面的指南。對於正在尋求在解決問題時優化資源的研究人員來說，它是一個全面的指南。自然啟發的優化演算法是非傳統的，這使它們比傳統方法更高效。

Dr. Vasuki A is currently working as Professor in the Department of Mechatronics Engineering at Kumaraguru College of Technology, Coimbatore, India. She has more than 27 years of teaching, research and academic administration experience. She has completed B.E in Electronics and Communication Engineering from PSG College of Technology in 1989. She has completed her postgraduate degree M.E Applied Electronics from Coimbatore Institute of Technology in 1991. She has done her Ph.D in Image Compression from PSG College of Technology under Anna University Chennai in 2010. Her research interests are Signal Processing, Image Processing, Communication and Optimization. She has published 3 Book Chapters, 38 National and International Journal papers and 60 National and International Conference papers. She has guided 30 PG projects and 50 UG projects. She is an approved Research Supervisor under Anna University Chennai and is currently guiding 9 research scholars.

Dr. Vasuki A目前在印度康伊馬托爾的Kumaraguru科技學院機電工程系擔任教授。她擁有超過27年的教學、研究和學術管理經驗。她於1989年從PSG科技學院獲得電子與通訊工程學士學位，並於1991年在康伊馬托爾科技學院完成應用電子學碩士學位。她於2010年在安娜大學金奈的PSG科技學院完成了圖像壓縮的博士學位。她的研究興趣包括信號處理、圖像處理、通訊和優化。她已發表了3篇專書章節、38篇國內外期刊論文和60篇國內外會議論文。她指導了30個碩士項目和50個本科項目。她是安娜大學金奈的研究主管，目前指導著9名研究學者。