محاسبات تکاملی: تکنیک‌ها و کاربردها

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. Covering both the theory and applications of evolutionary computation, the book offers exhaustive coverage of several topics on nontraditional evolutionary techniques, details working principles of new and popular evolutionary algorithms, and discusses case studies on both scientific and real-world applications of optimization 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 "This volume presents and discusses recent advancements in evolutionary computation of both theory and applications. Both scientific and engineering applications of evolutionary computation techniques are explored here. This book is broadly organized into three sections: theory and applications in engineering systems; theory and applications of single objective optimization; theory and applications of single and multi-objective optimization studies. Edited by professionals with years of experience, Evolutionary Computation: Techniques and Applications 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. Covering both the theory and applications of evolutionary computation, the book offers exhaustive coverage of several topics on nontraditional evolutionary techniques; covers detailed working principles of new and popular evolutionary algorithms; discusses case studies on both scientific and real-world applications of optimization. The book will be valuable faculty and researchers as well as advanced students in the areas of optimization, evolutionary computation, modeling and simulation, process plant simulation, and more."-- Provided by publisher