Ebook: Applied Nature-Inspired Computing: Algorithms and Case Studies
- Tags: Engineering, Computational Intelligence, Algorithm Analysis and Problem Complexity, Mathematics of Computing
- Series: Springer Tracts in Nature-Inspired Computing
- Year: 2020
- Publisher: Springer Singapore
- Edition: 1st ed. 2020
- Language: English
- pdf
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.