Nature-Inspired Computation in Engineering [electronic resource] /
edited by Xin-She Yang.
- 1st ed. 2016.
- X, 276 p. 54 illus., 34 illus. in color. online resource.
- Studies in Computational Intelligence, 637 1860-9503 ; .
- Studies in Computational Intelligence, 637 .
Flower Pollination Algorithm and its Applications in Engineering -- An Evolutionary Discrete Firefly Algorithm with Novel Operators for Solving the Vehicle Routing Problem with TimeWindows -- The Plant Propagation Algorithm for Discrete Optimisation: The Case of the Travelling Salesman Problem -- Enhancing Cooperative Coevolution with Surrogate-Assisted Local Search -- Cuckoo Search: From Cuckoo Reproduction Strategy to Combinatorial Optimization -- Clustering Optimization for WSN based on Nature-Inspired Algorithms -- Discrete Firefly Algorithm for Recruiting Task in a Swarm of Robots -- Nature-Inspired Swarm Intelligence for Data Fitting in Reverse Engineering: Recent Advances and FutureTrends -- A Novel Fast Optimisation Algorithm Using Differential Evolution Algorithm Optimisation and Meta- Modelling Approach -- A Hybridization of Runner-Based and Seed-Based Plant Propagation Algorithm -- Gravitational Search Algorithm Applied to Cell Formation Problem -- Parameterless Bat Algorithm and its Performace Study.
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. .
9783319302355
10.1007/978-3-319-30235-5 doi
Computational intelligence.
Artificial intelligence.
Computational Intelligence.
Artificial Intelligence.
Q342
006.3
Flower Pollination Algorithm and its Applications in Engineering -- An Evolutionary Discrete Firefly Algorithm with Novel Operators for Solving the Vehicle Routing Problem with TimeWindows -- The Plant Propagation Algorithm for Discrete Optimisation: The Case of the Travelling Salesman Problem -- Enhancing Cooperative Coevolution with Surrogate-Assisted Local Search -- Cuckoo Search: From Cuckoo Reproduction Strategy to Combinatorial Optimization -- Clustering Optimization for WSN based on Nature-Inspired Algorithms -- Discrete Firefly Algorithm for Recruiting Task in a Swarm of Robots -- Nature-Inspired Swarm Intelligence for Data Fitting in Reverse Engineering: Recent Advances and FutureTrends -- A Novel Fast Optimisation Algorithm Using Differential Evolution Algorithm Optimisation and Meta- Modelling Approach -- A Hybridization of Runner-Based and Seed-Based Plant Propagation Algorithm -- Gravitational Search Algorithm Applied to Cell Formation Problem -- Parameterless Bat Algorithm and its Performace Study.
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. .
9783319302355
10.1007/978-3-319-30235-5 doi
Computational intelligence.
Artificial intelligence.
Computational Intelligence.
Artificial Intelligence.
Q342
006.3