1st Edition

Computational Intelligence-based Optimization Algorithms From Theory to Practice

By Babak Zolghadr-Asli Copyright 2024
356 Pages 59 B/W Illustrations
by CRC Press

356 Pages 59 B/W Illustrations
by CRC Press

356 Pages 59 B/W Illustrations
by CRC Press

Computational intelligence-based optimization methods, also known as metaheuristic optimization algorithms, are a popular topic in mathematical programming. These methods have bridged the gap between various approaches and created a new school of thought to solve real-world optimization problems. In this book, we have selected some of the most effective and renowned algorithms in the... Read more

1. An Introduction to Meta-Heuristic Optimization

2. Pattern Search Algorithm

3. Genetic Algorithm

4. Simulated Annealing Algorithm

5. Tabu Search Algorithm

6. Ant Colony Optimization Algorithm

7. Particle Swarm Optimization Algorithm

8. Differential Evolution Algorithm

9. Harmony Search Algorithm

10. Shuffled Frog-Leaping Algorithm

11. Invasive Weed Optimization Algorithm

12. Biogeography-Based Optimization Algorithm

13. Cuckoo Search Algorithm

14. Firefly Algorithm

15. Gravitational Search Algorithm

16. Plant Propagation Algorithm

17. Teaching-Learning-Based Optimization Algorithm

18. Bat Algorithm

19. Flower Pollination Algorithm

20. Water Cycle Algorithm

21. Symbiotic Organisms Search Algorithm

Biography

Babak Zolghadr-Asli is currently a joint researcher under the QUEX program, working at the Sustainable Minerals Institute at The University of Queensland in Australia and The Centre for Water Systems at The University of Exeter in the UK. His primary research interest is to incorporate computational and artificial intelligence to understand the sustainable management of water resources.