Nature-Inspired Computation in Engineering Gebunden

This timely review book summarizes the state-of-the-art developments in nature-inspired optimization algorithms and their applications in engineering. Algorithms and topics include the overview and history of nature-inspired algorithms discrete firefly algorithm discrete cuckoo search plant propagation algorithm parameter-free bat algorithm gravitational search biogeography-based algorithm differential evolution particle swarm optimization and others. Applications include vehicle routing swarming robots discrete and combinatorial optimization clustering of wireless sensor networks cell formation economic load dispatch metamodeling surrogated-assisted cooperative co-evolution data fitting and reverse engineering as well as other case studies in engineering. This book will be an ideal reference for researchers lecturers graduates and engineers who are interested in nature-inspired computation artificial intelligence and computational intelligence. It can also serve as a reference for relevant courses in computer science artificial intelligence and machine learning natural computation engineering optimization and data mining.