Swarm Intelligence Algorithms (Two Volume Set): 1st Edition (Hardback) book cover

Swarm Intelligence Algorithms (Two Volume Set)

1st Edition

Edited by Adam Slowik

CRC Press

768 pages | 82 B/W Illus.

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Hardback: 9780367023454
pub: 2020-07-30
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Description

Swarm intelligence algorithms are a form of nature-based optimization algorithms. Their main inspiration is the cooperative behavior of animals within specific communities. This can be described as simple behaviors of individuals along with the mechanisms for sharing knowledge between them, resulting in the complex behavior of the entire community. Examples of such behavior can be found in ant colonies, bee swarms, schools of fish or bird flocks. Swarm intelligence algorithms are used to solve difficult optimization problems for which there are no exact solving methods or the use of such methods is impossible, e.g. due to unacceptable computational time.

This set comprises two volumes: Swarm Intelligence Algorithms: A Tutorial and Swarm Intelligence Algorithms: Modifications and Applications.

The first volume thoroughly presents the basics of 24 algorithms selected from the entire family of swarm intelligence algorithms. It contains a detailed explanation of how each algorithm works, along with relevant program codes in Matlab and the C ++ programming language, as well as numerical examples illustrating step-by-step how individual algorithms work.

The second volume describes selected modifications of these algorithms and presents their practical applications. This book presents 24 swarm algorithms together with their modifications and practical applications. Each chapter is devoted to one algorithm. It contains a short description along with a pseudo-code showing the various stages of its operation. In addition, each chapter contains a description of selected modifications of the algorithm and shows how it can be used to solve a selected practical problem.

Table of Contents

Volume 1:

1 Ant Colony Optimization

Pushpendra Singh, Nand K. Meena, Jin Yang, and Adam Slowik

2 Arti□cial Bee Colony Algorithm

Bahriye Akay and Dervis Karaboga

3 Bacterial Foraging Optimization

Sonam Parashar, Nand K. Meena, Jin Yang, and Neeraj Kanwar

4 Bat Algorithm

Xin-She Yang and Adam Slowik

5 Cat Swarm Optimization

Dorin Moldovan, Viorica Chifu, Ioan Salomie, and Adam Slowik

6 Chicken Swarm Optimization

Dorin Moldovan and Adam Slowik

7 Cockroach Swarm Optimization

Joanna Kwiecien

8 Crow Search Algorithm

Adam Slowik and Dorin Moldovan

9 Cuckoo Search Algorithm

Xin-She Yang and Adam Slowik

10 Dynamic Virtual Bats Algorithm

Ali Osman Topal

11 Dispersive Flies Optimisation: A Tutorial

Mohammad Majid al-Rifaie

12 Elephant Herding Optimization

Nand K. Meena, Jin Yang, and Adam Slowik

13 Fire□y Algorithm

Xin-She Yang and Adam Slowik

14 Glowworm Swarm Optimization - A Tutorial

Krishnanand Kaipa and Debasish Ghose

15 Grasshopper Optimization Algorithm

Szymon Šukasik

16 Grey Wolf Optimizer

Ahmed F. Ali and Mohamed A. Tawhid

17 Hunting Search Algorithm

Ferhat Erdal and Osman Tunca

18 Krill Herd Algorithm

Ali R. Kashani, Charles V. Camp, Hamed Tohidi, and Adam Slowik

19 Monarch Butter□y Optimization

Pushpendra Singh, Nand K. Meena, Jin Yang, and Adam Slowik

20 Particle Swarm Optimization

Adam Slowik

21 Salp Swarm Optimization: Tutorial

Essam H. Houssein, Ibrahim E. Mohamed , and Aboul Ella Hassanien

22 Social Spider Optimization

Ahmed F. Ali and Mohamed A. Tawhid

23 Stochastic Di□usion Search: A Tutorial

Mohammad Majid al-Rifaie and J. Mark Bishop

24 Whale Optimization Algorithm

Ali R. Kashani, Charles V. Camp, Moein Armanfar, and Adam Slowik

Volume 2:

1 Ant Colony Optimization, Modi□cations, and Application

Pushpendra Singh, Nand K. Meena, and Jin Yang

2 Arti□cial Bee Colony - Modi□cations and An Application to Software Requirements Selection

Bahriye Akay

3 Modi□ed Bacterial Forging Optimization and Application

Neeraj Kanwar, Nand K. Meena, Jin Yang, and Sonam Parashar

4 Bat Algorithm - Modi□cations and Application

Neeraj Kanwar, Nand K. Meena, and Jin Yang

5 Cat Swarm Optimization - Modi□cations and Application

Dorin Moldovan, Adam Slowik, Viorica Chifu, and Ioan Salomie

6 Chicken Swarm Optimization - Modi□cations and Application

Dorin Moldovan and Adam Slowik

7 Cockroach Swarm Optimization □ Modi□cations and Application

Joanna Kwiecien

8 Crow Search Algorithm - Modi□cations and Application

Adam Slowik and Dorin Moldovan

9 Cuckoo Search Optimisation □ Modi□cations and Application

Dhanraj Chitara, Nand K. Meena, and Jin Yang

10 Improved Dynamic Virtual Bats Algorithm for Identifying a Suspension System Parameters

Ali Osman Topal

11 Dispersive Flies Optimisation: Modi□cations and Application

Mohammad Majid al-Rifaie, Hooman Oroojeni M. J., and Mihalis Nicolaou

12 Improved Elephant Herding Optimization and Application

Nand K. Meena and Jin Yang

13 Fire□y Algorithm: Variants and Applications

Xin-She Yang

14 Glowworm Swarm Optimization - Modi□cations and Applications

Krishnanand Kaipa and Debasish Ghose

15 Grasshopper Optimization Algorithm - Modi□cations and Applications

Szymon Šukasik

16 Grey wolf optimizer □ Modi□cations and Applications

Ahmed F. Ali and Mohamed A. Tawhid

17 Hunting Search Optimization Modi□cation and Application

Ferhat Erdal, Osman Tunca, and Erkan Dogan

18 Krill Herd Algorithm □ Modi□cations and Applications

Ali R. Kashani, Charles V. Camp, Hamed Tohidi, and Adam Slowik

19 Modi□ed Monarch Butter□y Optimization and Real-life Applications

Pushpendra Singh, Nand K. Meena, and Jin Yang

20 Particle Swarm Optimization □ Modi□cations and Application

Adam Slowik

21 Salp Swarm Algorithm: Modi□cation and Application

Essam H. Houssein, Ibrahim E. Mohamed , and Aboul Ella Hassanien

22 Social Spider Optimization □ Modi□cations and Applications

Ahmed F. Ali and Mohamed A. Tawhid

23 Stochastic Di□usion Search: Modi□cations and Application

Mohammad Majid al-Rifaie and J. Mark Bishop

24 Whale Optimization Algorithm □ Modi□cations and Applications

Ali R. Kashani, Charles V. Camp, Moein Armanfar, and Adam Slowik

About the Editor

Adam Slowik (IEEE Member 2007; IEEE Senior Member 2012) is an Associate Professor in the Department of Electronics and Computer Science, Koszalin University of Technology. His research interests include soft computing, computational intelligence, and, particularly, bio-inspired optimization algorithms and their engineering applications. He was a recipient of one Best Paper Award (IEEE Conference on Human System Interaction - HSI 2008).

Subject Categories

BISAC Subject Codes/Headings:
COM059000
COMPUTERS / Computer Engineering
MAT004000
MATHEMATICS / Arithmetic
TEC007000
TECHNOLOGY & ENGINEERING / Electrical
TEC008000
TECHNOLOGY & ENGINEERING / Electronics / General