<P>Edited by professionals with years of experience, this book<B> </B>provides an introduction to the theory of evolutionary algorithms and single- and multi-objective optimization, and then goes on to discuss to explore applications of evolutionary algorithms for many uses with real-world applicati
Evolutionary computation. Techniques and applications
β Scribed by Babu, B. V.; Gujarathi, Ashish M (ed.)
- Publisher
- Apple Academic Press
- Year
- 2017
- Tongue
- English
- Leaves
- 652
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Table of Contents
Cover......Page 1
Half Title......Page 2
Title Page......Page 4
Copyright Page......Page 5
Contents......Page 6
List of Contributors......Page 10
List of Abbreviations......Page 14
Preface......Page 20
About the Editors......Page 24
PART 1. THEORY AND APPLICATIONS IN ENGINEERING SYSTEMS......Page 26
1. Introduction......Page 28
2. Bio-Mimetic Adaptations of Genetic Algorithm and Their Applications to Chemical Engineering......Page 46
3. Surrogate-Assisted Evolutionary Computing Methods......Page 80
4. Evolutionary Algorithms in Ironmaking Applications......Page 106
5. Harmony Search Optimization for Multilevel Thresholding in Digital Images......Page 138
6. Swarm Intelligence in Software Engineering Design Problems......Page 188
7. Gene Expression Programming in Nanotechnology Applications......Page 220
PART 2. THEORY AND APPLICATIONS OF SINGLE OBJECTIVE OPTIMIZATION STUDIES......Page 236
8. An Alternate Hybrid Evolutionary Method for Solving MINLP Problems......Page 238
9. Differential Evolution for Optimal Design of Shell-and-Tube Heat Exchangers......Page 264
10. Evolutionary Computation Based QoS-Aware Multicast Routing......Page 294
11. Performance Assessment of the Canonical Genetic Algorithm: A Study on Parallel Processing Via GPU Architecture......Page 326
12. An Efficient Approach for Populating Deep Web Repositories Using SFLA......Page 346
13. Closed Loop Simulation of Quadruple Tank Process Using Adaptive Multi-Loop Fractional Order PID Controller Optimized Using Bat Algorithm......Page 374
PART 3. THEORY AND APPLICATIONS OF SINGLE AND MULTIOBJECTIVE OPTIMIZATION STUDIES......Page 398
14. A Practical Approach Towards Multiobjective Shape Optimization......Page 400
15. Nature-Inspired Computing Techniques for Integer Factorization......Page 426
16. Genetic Algorithm Based Real-Time Parameter Identifier for an Adaptive Power System Stabilizer......Page 446
17. Applied Evolutionary Computation in Fire Safety Upgrading......Page 486
18. Elitist Multiobjective Evolutionary Algorithms for Voltage and Reactive Power Optimization in Power Systems......Page 508
19. Evaluation of Simulated Annealing, Differential Evolution and Particle Swarm Optimization for Solving Pooling Problems......Page 538
20. Performance Improvement of NSGA-II Algorithm by Modifying Crossover Probability Distribution......Page 570
21. Evolutionary Algorithms for Malware Detection and Classification......Page 594
Index......Page 636
β¦ Subjects
EvolutionΓ€rer Algorithmus
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<P>Edited by professionals with years of experience, this book<B> </B>provides an introduction to the theory of evolutionary algorithms and single- and multi-objective optimization, and then goes on to discuss to explore applications of evolutionary algorithms for many uses with real-world applicati
<P>Edited by professionals with years of experience, this book<B> </B>provides an introduction to the theory of evolutionary algorithms and single- and multi-objective optimization, and then goes on to discuss to explore applications of evolutionary algorithms for many uses with real-world applicati
<P>Edited by professionals with years of experience, this book<B> </B>provides an introduction to the theory of evolutionary algorithms and single- and multi-objective optimization, and then goes on to discuss to explore applications of evolutionary algorithms for many uses with real-world applicati
Edited by professionals with years of experience, this book provides an introduction to the theory of evolutionary algorithms and single- and multi-objective optimization, and then goes on to discuss to explore applications of evolutionary algorithms for many uses with real-world applications. Cover