There have been many recent developments related to fuzzy logic applications. This book, volume 749 in Springer’s “Studies in Computational Intelligence” series, contains research papers related to fuzzy logic, neural networks, and metaheuristics for optimization. It covers their use in diverse areas such as intelligent control, robotics, pattern recognition, medical diagnosis, time series prediction, and optimization.

The book has seven parts (38 chapters). The first part studies the use of type-2 fuzzy logic in metaheuristics. Its five chapters describe type-2 fuzzy logic applications related to the grey wolf optimizer algorithm, the optimization of neural networks, harmony search, bio-inspired techniques, and evolutionary algorithms. The second part concentrates on the theory and application of neural networks. The four chapters study applications related to biometrics, the melting points of liquids, walking patterns, and pattern recognition. The third part, “Metaheuristics,” has five chapters. The applications discussed include the tuning of support vector machine (SVM) classifiers, mathematical optimization, protein folding, particle hydrodynamics, and symbolic regression. The fourth part, “Fuzzy Control,” has five chapters. One chapter discusses the problem of determining uncertainty in control applications, while the rest look at applications in mobile robotics.

The fifth part discusses applications of fuzzy logic. The six chapters focus on recommender systems, money management, fuzzy sets, blood pressure diagnosis, hypertension, and the biomass of leaves. Part 6 covers evolutionary algorithms and optimization. Its five chapters look at project portfolio selection, vehicle routing, evolutionary algorithms for multi-objective optimization, and multi-user intelligent systems. The seventh (and last) part of the book consists of eight chapters on hybrid algorithms. The topics covered include translating natural language queries, predicting protein structures, querying databases, the Mexican stock exchange, vertex separation, disaster management, pattern classification, and classifying colors.

The book is highly technical and suitable primarily for experts in computational intelligence. Both theory and practice are equally well emphasized. The book may be useful for scholars trying to identify research topics related to areas such as fuzzy logic, neural networks, and optimization. Many interesting real-world applications greatly enhance the utility of the book. The editors have done a good job of bringing related topics together under various headings. However, subject and author indices would make the book more useful. Nevertheless, I strongly recommend it for researchers in the field of computational intelligence. Readers should also look at another book by two of the editors [1].