Handbook of Moth-Flame Optimization Algorithm: Variants, Hybrids, Improvements, and Applications

Moth-Flame Optimization algorithm is an emerging meta-heuristic and has been widely used in both science and industry. Solving optimization problem using this algorithm requires addressing a number of challenges, including multiple objectives, constraints, binary decision variables, large-scale search space, dynamic objective function, and noisy parameters.

Handbook of Moth-Flame Optimization Algorithm: Variants, Hybrids, Improvements, and Applications provides an in-depth analysis of this algorithm and the existing methods in the literature to cope with such challenges.

Key Features:

• Reviews the literature of the Moth-Flame Optimization algorithm
• Provides an in-depth analysis of equations, mathematical models, and mechanisms of the Moth-Flame Optimization algorithm
• Proposes different variants of the Moth-Flame Optimization algorithm to solve binary, multi-objective, noisy, dynamic, and combinatorial optimization problems
• Demonstrates how to design, develop, and test different hybrids of Moth-Flame Optimization algorithm
• Introduces several applications areas of the Moth-Flame Optimization algorithm

This handbook will interest researchers in evolutionary computation and meta-heuristics and those who are interested in applying Moth-Flame Optimization algorithm and swarm intelligence methods overall to different application areas.

《蛾火優化演算法手冊：變體、混合、改進與應用》是一本深入分析蛾火優化演算法及其應對挑戰的文獻方法的書籍。蛾火優化演算法是一種新興的元啟發式演算法，廣泛應用於科學和工業領域。使用這種演算法解決優化問題需要應對多目標、約束、二進制決策變量、大規模搜索空間、動態目標函數和噪聲參數等多個挑戰。

本手冊的主要特點包括：
- 回顧蛾火優化演算法的文獻
- 深入分析蛾火優化演算法的方程式、數學模型和機制
- 提出不同的蛾火優化演算法變體，以解決二進制、多目標、噪聲、動態和組合優化問題
- 示範如何設計、開發和測試不同的蛾火優化演算法混合方法
- 介紹蛾火優化演算法的幾個應用領域

這本手冊將對進化計算和元啟發式演算法的研究人員以及對將蛾火優化演算法和群體智能方法應用於不同應用領域感興趣的人具有重要意義。

Seyedali Mirjalili is a Professor at Torrens University Center for Artificial Intelligence Research and Optimization and internationally recognized for his advances in nature-inspired Artificial Intelligence (AI) techniques. He is the author of more than 300 publications including five books, 250 journal articles, 20 conference papers, and 30 book chapters. With more than 50,000 citations and H-index of 75, he is one of the most influential AI researchers in the world. From Google Scholar metrics, he is globally the most cited researcher in Optimization using AI techniques, which is his main area of expertise. Since 2019, he has been in the list of 1% highly-cited researchers and named as one of the most influential researchers in the world by Web of Science. In 2021, The Australian newspaper named him as the top researcher in Australia in three fields of Artificial Intelligence, Evolutionary Computation, and Fuzzy Systems. He is a senior member of IEEE and is serving as an editor of leading AI journals including Neurocomputing, Applied Soft Computing, Advances in Engineering Software, Computers in Biology and Medicine, Healthcare Analytics, and Applied Intelligence.

Seyedali Mirjalili是Torrens大學人工智慧研究與優化中心的教授，以其在自然啟發式人工智慧技術方面的進展而享譽國際。他是300多篇著作的作者，包括五本書、250篇期刊文章、20篇會議論文和30篇書籍章節。他的論文被引用超過50,000次，H指數為75，是世界上最有影響力的人工智慧研究者之一。根據Google Scholar的指標，他是全球最受引用的優化使用人工智慧技術的研究者，這是他的主要專業領域。自2019年以來，他一直在1%高引用研究者名單中，並被Web of Science評為世界上最有影響力的研究者之一。2021年，《澳大利亞人報》將他列為澳大利亞在人工智慧、進化計算和模糊系統三個領域的頂尖研究者。他是IEEE的高級會員，並擔任多個領先的人工智慧期刊的編輯，包括Neurocomputing、Applied Soft Computing、Advances in Engineering Software、Computers in Biology and Medicine、Healthcare Analytics和Applied Intelligence。