This book presents recent developments in a specific area of computational intelligence, namely fuzzy logic augmentation of nature-inspired optimization metaheuristics and their applications. It has two parts, each one consisting of a number of papers grouped around a common topic. The first part's seven papers deal mainly with theoretical aspects. They describe new, improved metaheuristic algorithms using fuzzy systems. Some of these algorithms are improved ant colony optimization (ACO) and particle swarm optimization (PSO) algorithms using fuzzy logic for dynamic parameter tuning; a new bat algorithm with fuzzy logic for dynamical parameter adaptation; a firefly algorithm applied for optimizing benchmark functions; a harmony search algorithm; and a cuckoo search algorithm.
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