Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing and Neural Networks

Citation

Rigelsford, J. (2000), "Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing and Neural Networks", Industrial Robot, Vol. 27 No. 5. https://doi.org/10.1108/ir.2000.04927eae.003

Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing and Neural Networks

D.T. Pham and D. KarabagaSpringer-Verlag2000302 pp.ISBN 1-85233-028-7£39.50Hardcover

Keywords Genetic algorithms, Tabu search, Neural networks

Intelligent Optimisation Techniques is aimed at engineers and gives a concise introduction to genetic algorithms, tabu search, simulated annealing and neural networks. The book presents a range of practical applications which are relevant to electronic, electrical, manufacturing, mechanical and systems engineering.

Comprising five chapters and six appendices, this book starts with an introduction to the different optimisation techniques and how they perform on test problems. Chapter 2 addresses genetic algorithms, which work in a similar manner to natural selection. Tabu search is a heuristic procedure that employs dynamically generated constraints and is discussed in chapter 3.

Chapters 4 and 5 discuss simulated annealing and neural networks, respectively. These use a technique similar to minimum energy configuration in metal annealing, and a computational model of the brain.

The appendices include classical optimisation algorithms, the concept of fuzzy sets and fuzzy logic control and listings of C programs which implement the main optimisation techniques.

This is a superbly written book which makes a potentially difficult subject easy to understand. The C programs are a good foundation for anyone wishing to implement genetic algorithms, tabu search, simulated annealing or neural networks.

Jon Rigelsford