Tenne, Yoel
Computational Intelligence in Expensive Optimization Problems
I. Techniques for Resource-Intensive Problems
1. A Survey of Fitness Approximation Methods Applied in Evolutionary Algorithms
L. Shi, K. Rasheed
2. A Review of Techniques for Handling Expensive Functions in Evolutionary Multi-Objective Optimization
Luis V. Santana-Quintero, Alfredo Arias Montaño, Carlos A. Coello Coello
3. Multilevel Optimization Algorithms Based on Metamodel- and Fitness Inheritance-Assisted Evolutionary Algorithms
Kyriakos C. Giannakoglou, Ioannis C. Kampolis
4. Knowledge-Based Variable-Fidelity Optimization of Expensive Objective Functions through Space Mapping
Slawomir Koziel, John W. Bandler
5. Reducing Function Evaluations Using Adaptively Controlled Differential Evolution with Rough Approximation Model
Tetsuyuki Takahama, Setsuko Sakai
6. Kriging Is Well-Suited to Parallelize Optimization
David Ginsbourger, Rodolphe Riche, Laurent Carraro
7. Analysis of Approximation-Based Memetic Algorithms for Engineering Optimization
Frederico Gadelha Guimarães, David Alister Lowther, Jaime Arturo Ramírez
8. Opportunities for Expensive Optimization with Estimation of Distribution Algorithms
Alberto Ochoa
9. On Similarity-Based Surrogate Models for Expensive Single- and Multi-objective Evolutionary Optimization
L. G. Fonseca, H. J. C. Barbosa, A. C. C. Lemonge
10. Multi-objective Model Predictive Control Using Computational Intelligence
Hirotaka Nakayama, Yeboon Yun, Masakazu Shirakawa
11. Improving Local Convergence in Particle Swarms by Fitness Approximation Using Regression
Stefan Bird, Xiaodong Li
II. Techniques for High-Dimensional Problems
12. Differential Evolution with Scale Factor Local Search for Large Scale Problems
Andrea Caponio, Anna V. Kononova, Ferrante Neri
13. Large-Scale Network Optimization with Evolutionary Hybrid Algorithms: Ten Years’ Experience with the Electric Power Distribution Industry
Pedro M. S. Carvalho, Luis A. F. M. Ferreira
14. A Parallel Hybrid Implementation Using Genetic Algorithms, GRASP and Reinforcement Learning for the Salesman Traveling Problem
João Paulo Queiroz Santos, Francisco Chagas Lima Júnior, Rafael Marrocos Magalhães, Jorge Dantas Melo, Adrião Duarte Doria Neto
15. An Evolutionary Approach for the TSP and the TSP with Backhauls
Haldun Süral, Nur Evin Özdemirel, Ýlter Önder, Meltem Sönmez Turan
16. Towards Efficient Multi-objective Genetic Takagi-Sugeno Fuzzy Systems for High Dimensional Problems
Marco Cococcioni, Beatrice Lazzerini, Francesco Marcelloni
17. Evolutionary Algorithms for the Multi Criterion Minimum Spanning Tree Problem
Madeleine Davis-Moradkhan, Will Browne
18. Loss-Based Estimation with Evolutionary Algorithms and Cross-Validation
David Shilane, Richard H. Liang, Sandrine Dudoit
III. Real-World Applications
19. Particle Swarm Optimisation Aided MIMO Transceiver Designs
S. Chen, W. Yao, H. R. Palally, L. Hanzo
20. Optimal Design of a Common Rail Diesel Engine Piston
Teresa Donateo
21. Robust Preliminary Space Mission Design under Uncertainty
Massimiliano Vasile, Nicolas Croisard
22. Progressive Design Methodology for Design of Engineering Systems
Praveen Kumar, Pavol Bauer
23. Reliable Network Design Using Hybrid Genetic Algorithm Based on Multi-Ring Encoding
Jin-Myung Won, Alice Malisia, Fakhreddine Karray
24. Isolated Word Analysis Using Biologically-Based Neural Networks
Walter M. Yamada, Theodore W. Berger
25. A Distributed Evolutionary Approach to Subtraction Radiography
Gabriel Mañana Guichón, Eduardo Romero Castro
26. Speeding-Up Expensive Evaluations in High-Level Synthesis Using Solution Modeling and Fitness Inheritance
Christian Pilato, Daniele Loiacono, Antonino Tumeo, Fabrizio Ferrandi, Pier Luca Lanzi, Donatella Sciuto
Keywords: Engineering, Appl.Mathematics/Computational Methods of Engineering, Artificial Intelligence (incl. Robotics), Applications of Mathematics
- Author(s)
- Tenne, Yoel
- Goh, Chi-Keong
- Publisher
- Springer
- Publication year
- 2010
- Language
- en
- Edition
- 1
- Series
- Evolutionary Learning and Optimization
- Category
- Technology, Energy, Traffic
- Format
- Ebook
- eISBN (PDF)
- 9783642107016