Differential Evolution: Fundamentals and Applications in Electrical Engineering (Hardcover)

Anyong Qing


Differential evolution is a very simple but very powerful stochastic optimizer. Since its inception, it has proved very efficient and robust in function optimization and has been applied to solve problems in many scientific and engineering fields. In Differential Evolution , Dr. Qing begins with an overview of optimization, followed by a state-of-the-art review of differential evolution, including its fundamentals and up-to-date advances. He goes on to explore the relationship between differential evolution strategies, intrinsic control parameters, non-intrinsic control parameters, and problem features through a parametric study. Findings and recommendations on the selection of strategies and intrinsic control parameter values are presented. Lastly, after an introductory review of reported applications in electrical and electronic engineering fields, different research groups demonstrate how the methods can be applied to such areas as: multicast routing, multisite mapping in grid environments, antenna arrays, analog electric circuit sizing, electricity markets, stochastic tracking in video sequences, and color quantization.

  • Contains a systematic and comprehensive overview of differential evolution
  • Reviews the latest differential evolution research
  • Describes a comprehensive parametric study conducted over a large test bed
  • Shows how methods can be practically applied to
    • mobile communications
    • grid computing
    • circuits
    • image processing
    • power engineering
  • Sample applications demonstrated by research groups in the United Kingdom, Australia, Italy, Turkey, China, and Eastern Europe
  • Provides access to companion website with code examples for download

Differential Evolution is ideal for application engineers, who can use the methods described to solve specific engineering problems. It is also a valuable reference for post-graduates and researchers working in evolutionary computation, design optimization and artificial intelligence. Researchers in the optimization field or engineers and managers involved in operations research will also find the book a helpful introduction to the topic.


差分進化是一種非常簡單但非常強大的隨機優化器。自從它的誕生以來,在函數優化方面它已被證明非常高效和穩健,並且已應用於解決許多科學和工程領域的問題。在《差分進化》一書中,Qing 博士首先概述了優化的概念,然後對差分進化進行了最新的綜述,包括其基礎知識和最新進展。他進一步通過參數研究探討了差分進化策略、內在控制參數、非內在控制參數和問題特徵之間的關係。書中還提出了關於策略和內在控制參數值選擇的研究結果和建議。最後,在對電氣和電子工程領域的報告應用進行簡要回顧之後,不同的研究團隊展示了這些方法如何應用於多點傳送路由、網格環境中的多站點映射、天線陣列、類比電路尺寸調整、電力市場、視頻序列中的隨機跟踪和顏色量化等領域。

- 包含對差分進化的系統性和全面的概述
- 回顧了最新的差分進化研究
- 通過對大型測試床進行全面的參數研究
- 展示了方法如何在實際應用中使用,包括移動通信、網格計算、電路、圖像處理和電力工程等領域
- 由英國、澳大利亞、意大利、土耳其、中國和東歐的研究團隊展示了樣本應用
- 提供了附帶代碼示例的伴隨網站供下載