Nature Inspired Computation in Engineering 1st Edition by Xin She Yang 3319302353 9783319302355

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ISBN 10:3319302353 
ISBN 13:9783319302355
Author:Xin She Yang

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 serveas a reference for relevant courses in computer science, artificial intelligence and machine learning, natural computation, engineering optimization and data mining.

Nature Inspired Computation in Engineering 1st Table of contents:

Nature-Inspired Optimization Algorithms in Engineering: Overview and Applications

An Evolutionary Discrete Firefly Algorithm with Novel Operators for Solving the Vehicle Routing Problem with Time Windows

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 Future Trends

A Novel Fast Optimisation Algorithm Using Differential Evolution Algorithm Optimisation and Meta-Modelling Approach

A Hybridisation of Runner-Based and Seed-Based Plant Propagation Algorithms

Economic Load Dispatch Using Hybrid MpBBO-SQP Algorithm

Gravitational Search Algorithm Applied to the Cell Formation Problem

Parameterless Bat Algorithm and Its Performance Study

 

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