This book is a delight for academics, researchers and professionals working in evolutionary and swarm computing, computational intelligence, machine learning and engineering design, as well as search and optimization in general. It provides an introduction to the design and development of a number o
Evolutionary and Swarm Intelligence Algorithms
β Scribed by Jagdish Chand Bansal, Pramod Kumar Singh, Nikhil R. Pal
- Publisher
- Springer International Publishing
- Year
- 2019
- Tongue
- English
- Leaves
- 194
- Series
- Studies in Computational Intelligence 779
- Edition
- 1st ed.
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
This book is a delight for academics, researchers and professionals working in evolutionary and swarm computing, computational intelligence, machine learning and engineering design, as well as search and optimization in general. It provides an introduction to the design and development of a number of popular and recent swarm and evolutionary algorithms with a focus on their applications in engineering problems in diverse domains. The topics discussed include particle swarm optimization, the artificial bee colony algorithm, Spider Monkey optimization algorithm, genetic algorithms, constrained multi-objective evolutionary algorithms, genetic programming, and evolutionary fuzzy systems. A friendly and informative treatment of the topics makes this book an ideal reference for beginners and those with experience alike.
β¦ Table of Contents
Front Matter ....Pages i-x
Swarm and Evolutionary Computation (Jagdish Chand Bansal, Nikhil R. Pal)....Pages 1-9
Particle Swarm Optimization (Jagdish Chand Bansal)....Pages 11-23
Artificial Bee Colony Algorithm Variants and Its Application to Colormap Quantization (Bahriye Akay, Kader Demir)....Pages 25-41
Spider Monkey Optimization Algorithm (Harish Sharma, Garima Hazrati, Jagdish Chand Bansal)....Pages 43-59
Genetic Algorithm and Its Advances in Embracing Memetics (Liang Feng, Yew-Soon Ong, Abhishek Gupta)....Pages 61-84
Constrained Multi-objective Evolutionary Algorithm (Kalyanmoy Deb)....Pages 85-118
Genetic Programming for Classification and Feature Selection (Kaustuv Nag, Nikhil R. Pal)....Pages 119-141
Genetic Programming for Job Shop Scheduling (Su Nguyen, Mengjie Zhang, Mark Johnston, Kay Chen Tan)....Pages 143-167
Evolutionary Fuzzy Systems: A Case Study for Intrusion Detection Systems (S. Elhag, A. FernΓ‘ndez, S. Alshomrani, F. Herrera)....Pages 169-190
β¦ Subjects
Engineering; Computational Intelligence; Artificial Intelligence (incl. Robotics)
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