book

Swarm Intelligence Algorithms

Name: Swarm Intelligence Algorithms
Author: Adam Slowik
ISBN: 9780429749506

by Adam Slowik

August 2020

Intermediate to advanced

362 pages

12h 58m

English

CRC Press

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1. Ant Colony Optimization
1.1 Introduction
1.2 Ants’ behavior
1.3 Ant colony algorithm
1.4 Source-code of ACO algorithm in Matlab
1.5 Source-code of ACO algorithm in C++
1.6 Step-by-step numerical example of ACO algorithm
1.7 Conclusion
Acknowledgment
ReferencesReferencesReferencesReferencesReferencesReferencesReferencesReferencesReferencesReferencesReferencesReferencesReferencesReferencesReferencesReferencesReferencesReferencesReferencesReferencesReferencesReferencesReferencesReferences
2. Artificial Bee Colony Algorithm
2.1 Introduction
2.2 The original ABC algorithm
2.3 Source-code of ABC algorithm in Matlab
2.4 Source-code of ABC algorithm in C++
2.5 Step-by-step numerical example of the ABC algorithm
2.6 Conclusions
3. Bacterial Foraging Optimization
3.1 Introduction
3.2 Bacterial foraging optimization algorithm
3.2.1 Chemotaxis
3.2.2 Swarming
3.2.3 Reproduction
3.2.4 Elimination and dispersal3.3 Pseudo-code of bacterial foraging optimization
3.4 Matlab source-code of bacterial foraging optimization
3.5 Numerical examples
3.6 Conclusions
3.7 Acknowledgement
4. Bat Algorithm
4.1 Introduction
4.2 Original bat algorithm
4.2.1 Description of the bat algorithm
4.2.2 Pseudo-code of BA
4.2.3 Parameters in the bat algorithm
4.3 Source code of bat algorithm in Matlab
4.4 Source code in C++
4.5 A worked example
4.6 Conclusion
5. Cat Swarm Optimization
5.1 Introduction
5.2 Original CSO algorithm
5.2.1 Pseudo-code of global version of CSO algorithm
5.2.2 Description of global version of CSO algorithm
5.2.2.1 Seeking mode (resting)
5.2.2.2 Tracing mode (movement)
5.2.3 Description of local version of CSO algorithm
5.3 Source-code of global version of CSO algorithm in Matlab
5.4 Source-code of global version of CSO algorithm in C++
5.5 Step-by-step numerical example of global version of CSO algorithm
5.6 Conclusions
6. Chicken Swarm Optimization
6.1 Introduction
6.2 Original CSO algorithm
6.2.1 Pseudo-code of global version of CSO algorithm
6.2.2 Description of global version of CSO algorithm
6.3 Source-code of global version of CSO algorithm in Matlab
6.4 Source-code of global version of CSO algorithm in C++
6.5 Step-by-step numerical example of global version of CSO algorithm
6.6 Conclusions
7. Cockroach Swarm Optimization
7.1 Introduction
7.2 Original cockroach swarm optimization algorithm
7.2.1 Pseudo-code of CSO algorithm
7.2.2 Description of the CSO algorithm
7.3 Source-code of CSO algorithm in Matlab
7.4 Source-code of CSO algorithm in C++
7.5 Step-by-step numerical example of CSO algorithm
7.6 Conclusions
8. Crow Search Algorithm
8.1 Introduction
8.2 Original CSA
8.3 Source-code of CSA in Matlab
8.4 Source-code of CSA in C++
8.5 Step-by-step numerical example of CSA
8.6 Conclusions
9. Cuckoo Search Algorithm
9.1 Introduction
9.2 Original cuckoo search
9.2.1 Description of the cuckoo search
9.2.2 Pseudo-code of CS
9.2.3 Parameters in the cuckoo search
9.3 Source code of the cuckoo search in Matlab
9.4 Source code in C++
9.5 A worked example
9.6 Conclusion
10. Dynamic Virtual Bats Algorithm
10.1 Introduction
10.2 Dynamic virtual bats algorithm
10.2.1 Pseudo-code of DVBA
10.2.2 Description of DVBA
10.3 Source-code of DVBA in Matlab
10.4 Source-code of DVBA in C++
10.5 Step-by-step numerical example of DVBA
10.6 Conclusions
11. Dispersive Flies Optimisation: A Tutorial
11.1 Introduction
11.2 Dispersive flies optimisation
11.3 Source code
11.3.1 Matlab
11.3.2 C++
11.3.3 Python
11.4 Numerical example: optimisation with DFO
11.5 Conclusion
12. Elephant Herding Optimization
12.1 Introduction
12.2 Elephant herding optimization
12.2.1 Position update of elephants in a clan
12.2.2 Separation of male elephants from the clan
12.2.3 Pseudo-code of EHO algorithm
12.3 Source-code of EHO algorithm in Matlab
12.4 Source-code of EHO algorithm in C++
12.5 Step-by-step numerical example of EHO algorithm
12.6 Conclusions
AcknowledgementAcknowledgement
13. Firefly Algorithm
13.1 Introduction
13.2 Original firefly algorithm
13.2.1 Description of the standard firefly algorithm
13.2.2 Pseudo-code of FA
13.2.3 Parameters in the firefly algorithm
13.3 Source code of firefly algorithm in Matlab
13.4 Source code in C++
13.5 A worked example
13.6 Handling constraints
13.7 Conclusion
14. Glowworm Swarm Optimization: A Tutorial
14.1 Introduction
14.1.1 Basic principle of GSO
14.1.2 The Glowworm Swarm Optimization (GSO) algorithm
14.1.3 Algorithm description
14.2 Source-code of GSO algorithm in Matlab
14.3 Source-code of GSO algorithm in C++
14.4 Step-by-step numerical example of GSO algorithm
14.5 Conclusions
15. Grasshopper Optimization Algorithm
15.1 Introduction
15.2 Description of the Grasshopper Optimization Algorithm
15.3 Source-code of GOA in Matlab
15.4 Source-code of GOA in C++
15.5 Step-by-step numerical example of GOA
15.6 Conclusion
16. Grey Wolf Optimizer
16.1 Introduction
16.2 Original GWO algorithm
16.2.1 Main concepts and inspiration16.2.2 Social hierarchy16.2.3 Encircling prey
16.2.4 Hunting process
16.2.5 Attacking prey (exploitation)
16.2.6 Search for prey (exploration)16.2.7 Pseudo-code of GWO algorithm
16.2.8 Description of the GWO algorithm
16.3 Source-code of GWO algorithm in Matlab
16.4 Source-code of GWO algorithm in C++
16.5 Step-by-step numerical example of GWO algorithm
16.6 Conclusion
17. Hunting Search Algorithm
17.1 Introduction
17.2 Original HuS algorithm
17.2.1 Pseudo-code and description of HuS algorithm
17.3 Source code of HuS algorithm in Matlab
17.4 Source code of HuS algorithm in C++
17.5 Elaboration on HuS algorithm with constrained minimization problem
17.6 Conclusion
18. Krill Herd Algorithm
18.1 Introduction
18.2 Original KH algorithm
18.2.1 Pseudo-code of the original version of KH algorithm
18.2.2 Description of the original version of KH algorithm
18.3 Source-code of the KH algorithm in Matlab
18.4 Source-code of the KH algorithm in C++
18.5 Step-by-step numerical example of KH algorithm (1/2)
18.5 Step-by-step numerical example of KH algorithm (2/2)
18.6 Conclusion
19. Monarch Butterfly Optimization
19.1 Introduction
19.2 Monarch butterfly optimization
19.2.1 Migration operator
19.2.2 Butterfly adjusting operator
19.3 Algorithm of monarch butterfly optimization
19.4 Source-code of MBO algorithm in Matlab
19.5 Source-code of MBO algorithm in C++
19.6 Step-by-step numerical example of MBO algorithm
19.7 Conclusion
20. Particle Swarm Optimization
20.1 Introduction
20.2 Original PSO algorithm
20.2.1 Pseudo-code of global version of PSO algorithm
20.2.2 Description of the global version of the PSO algorithm
20.2.3 Description of the local version of the PSO algorithm
20.3 Source-code of global version of PSO algorithm in Matlab
20.4 Source-code of global version of PSO algorithm in C++
20.5 Step-by-step numerical example of global version of PSO algorithm
20.6 Conclusions
21. Salp Swarm Algorithm: Tutorial
21.1 Introduction
21.2 Salp swarm algorithm (SSA)
21.2.1 Pseudo-code of SSA algorithm
21.2.2 Description of SSA algorithm
21.3 Source code of SSA algorithm in Matlab
21.4 Source-code of SSA algorithm in C++
21.5 Step-by-step numerical example of SSA algorithm
21.6 Conclusion
22. Social Spider Optimization
22.1 Introduction
22.2 Original SSO algorithm
22.2.1 Social behavior and inspiration22.2.2 Population initialization
22.2.3 Evaluation of the solution quality
22.2.4 Modeling of the vibrations through the communal web
22.2.5 Female cooperative operator
22.2.6 Male cooperative operator
22.2.7 Mating operator
22.2.8 Pseudo-code of SSO algorithm
22.2.9 Description of the SSO algorithm
22.3 Source-code of SSO algorithm in Matlab
22.4 Source-code of SSO algorithm in C++
22.5 Step-by-step numerical example of SSO algorithm
22.6 Conclusion
23. Stochastic Diffusion Search: A Tutorial
23.1 Introduction
23.2 Stochastic Diffusion Search
23.2.1 The mining game
23.2.2 Refinements in the metaphor
23.3 SDS architecture
23.4 Step by step example: text search
23.5 Source code
23.5.1 Matlab
23.5.2 C++
23.5.3 Python
23.6 Conclusion
24. Whale Optimization Algorithm
24.1 Introduction
24.2 Original WOA
24.2.1 Pseudo-code of the WOA
24.2.2 Description of the WOA
24.3 Source-code of the WOA in Matlab
24.4 Source-code of the WOA in C++
24.5 A step-by-step numerical example of WOA
24.6 Conclusions
Index

Content preview from Swarm Intelligence Algorithms

220 Hunting Search Algorithm

C++ programing language is demonstrated. In Sections 17.5 and 17.6, the

numerical example of the HuS algorithm and some conclusions are provided,

respectively.

17.2 Original HuS algorithm

In this section, the mentioned algorithm will be discussed with more detail.

Compared to hunting process, in an optimization problem each ‘hunter’ is

replaced with a ‘solution’ of the design problem. Note that group hunting and

our stochastic search algorithm have a primary diﬀerence. In group hunting

of lions, wolves, and dolphins, hunters can see the prey or when they hunt at

night at least they can sense the smell of the prey and determine ...

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