Applied Nature-Inspired Computing: Algorithms and Case Studies

This book presents a cutting-edge research procedure in the Nature-Inspired Computing (NIC) domain and its connections with computational intelligence areas in real-world engineering applications. It introduces readers to a broad range of algorithms, such as genetic algorithms, particle swarm optimization, the firefly algorithm, flower pollination algorithm, collision-based optimization algorithm, bat algorithm, ant colony optimization, and multi-agent systems. In turn, it provides an overview of meta-heuristic algorithms, comparing the advantages and disadvantages of each. Moreover, the book provides a brief outline of the integration of nature-inspired computing techniques and various computational intelligence paradigms, and highlights nature-inspired computing techniques in a range of applications, including: evolutionary robotics, sports training planning, assessment of water distribution systems, flood simulation and forecasting, traffic control, gene expression analysis, antenna array design, and scheduling/dynamic resource management.

Author: Nilanjan Dey, Amira S. Ashour, Siddhartha Bhattacharyya

Publisher: Springer

Publication Date: Aug 24, 2019

Number of Pages: NA pages

Language: English

Binding: Hardcover

ISBN-10: 9811392625

ISBN-13: 9789811392627