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Brain Storm Optimization Algorithms

Concepts, Principles and Applications

  • Shi Cheng
  • Yuhui Shi
Book

Part of the Adaptation, Learning, and Optimization book series (ALO, volume 23)

Table of contents

  1. Front Matter
    Pages i-xv
  2. Foundations

    1. Front Matter
      Pages 1-1
    2. Shi Cheng, Hui Lu, Xiujuan Lei, Yuhui Shi
      Pages 3-32
  3. Methodology

    1. Front Matter
      Pages 33-33
    2. Hui Lu, Rongrong Zhou, Shi Cheng, Yuhui Shi
      Pages 35-59
    3. Guojiang Xiong, Jing Zhang, Dongyuan Shi, Yu He
      Pages 61-77
  4. Applications

    1. Front Matter
      Pages 155-155
    2. Hui Lu, Chongchong Guan, Shi Cheng, Yuhui Shi
      Pages 157-188
    3. Liviu Mafteiu-Scai, Emanuela Mafteiu, Roxana Mafteiu-Scai
      Pages 189-220
    4. Satyabrata Dash, Deepak Joshi, Sukanta Dey, Meenali Janveja, Gaurav Trivedi
      Pages 221-243
  5. Back Matter
    Pages 299-299

About this book

Introduction

Brain Storm Optimization (BSO) algorithms are a new kind of swarm intelligence method, which is based on the collective behavior of human beings, i.e., on the brainstorming process. Since the introduction of BSO algorithms in 2011, many studies on them have been conducted. They not only offer an optimization method, but could also be viewed as a framework of optimization techniques. The process employed in the algorithms could be simplified as a framework with two basic operations: the converging operation and the diverging operation. A “good enough” optimum could be obtained through recursive solution divergence and convergence. The resulting optimization algorithm would naturally have the capability of both convergence and divergence.

This book is primarily intended for researchers, engineers, and graduate students with an interest in BSO algorithms and their applications. The chapters cover various aspects of BSO algorithms, and collectively provide broad insights into what these algorithms have to offer. The book is ideally suited as a graduate-level textbook, whereby students may be tasked with the study of the rich variants of BSO algorithms that involves a hands-on implementation to demonstrate the utility and applicability of BSO algorithms in solving optimization problems.   
 

Keywords

Computational Intelligence Evolutionary Computation Swarm Intelligence Brain Storm Optimization Optimization BSO

Editors and affiliations

  • Shi Cheng
    • 1
  • Yuhui Shi
    • 2
  1. 1.School of Computer ScienceShaanxi Normal UniversityXi’anChina
  2. 2.Shenzhen Key Laboratory of Computational Intelligence, Department of Computer Science and EngineeringSouthern University of Science and TechnologyShenzhenChina

Bibliographic information

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