In modern science and engineering, laboratory experiments are replaced by high fidelity and computationally expensive simulations. Using such simulations reduces costs and shortens development times but introduces new challenges to design optimization process. Examples of such challenges include limited computational resource for simulation runs, complicated response surface of the simulation inputs-outputs, and etc.
Under such difficulties, classical optimization and analysis methods may perform poorly. This motivates the application of computational intelligence methods such as evolutionary algorithms, neural networks and fuzzy logic, which often perform well in such settings. This is the first book to introduce the emerging field of computational intelligence in expensive optimization problems. Topics covered include:
- Dedicated implementations of evolutionary algorithms, neural networks and fuzzy logic.
- Reduction of expensive evaluations (modelling, variable-fidelity, fitness inheritance).
- Frameworks for optimization (model management, complexity control, model selection).
- Parallelization of algorithms (implementation issues on clusters, grids, parallel machines).
- Incorporation of expert systems and human-system interface.
- Single and multiobjective algorithms.
- Data mining and statistical analysis.
- Analysis of real-world cases (such as multidisciplinary design optimization).
The edited book provides both theoretical treatments and real-world insights gained by experience, all contributed by leading researchers in the respective fields. As such, it is a comprehensive reference for researchers, practitioners, and advanced-level students interested in both the theory and practice of using computational intelligence for expensive optimization problems.
Author(s): L. Shi, K. Rasheed (auth.), Yoel Tenne, Chi-Keong Goh (eds.)
Series: Adaptation Learning and Optimization 2
Edition: 1
Publisher: Springer-Verlag Berlin Heidelberg
Year: 2010
Language: English
Pages: 800
Tags: Appl.Mathematics/Computational Methods of Engineering; Artificial Intelligence (incl. Robotics); Applications of Mathematics
Front Matter....Pages -
Front Matter....Pages 1-1
A Survey of Fitness Approximation Methods Applied in Evolutionary Algorithms....Pages 3-28
A Review of Techniques for Handling Expensive Functions in Evolutionary Multi-Objective Optimization....Pages 29-59
Multilevel Optimization Algorithms Based on Metamodel- and Fitness Inheritance-Assisted Evolutionary Algorithms....Pages 61-84
Knowledge-Based Variable-Fidelity Optimization of Expensive Objective Functions through Space Mapping....Pages 85-109
Reducing Function Evaluations Using Adaptively Controlled Differential Evolution with Rough Approximation Model....Pages 111-129
Kriging Is Well-Suited to Parallelize Optimization....Pages 131-162
Analysis of Approximation-Based Memetic Algorithms for Engineering Optimization....Pages 163-191
Opportunities for Expensive Optimization with Estimation of Distribution Algorithms....Pages 193-218
On Similarity-Based Surrogate Models for Expensive Single- and Multi-objective Evolutionary Optimization....Pages 219-248
Multi-objective Model Predictive Control Using Computational Intelligence....Pages 249-264
Improving Local Convergence in Particle Swarms by Fitness Approximation Using Regression....Pages 265-293
Front Matter....Pages 295-295
Differential Evolution with Scale Factor Local Search for Large Scale Problems....Pages 297-323
Large-Scale Network Optimization with Evolutionary Hybrid Algorithms: Ten Years’ Experience with the Electric Power Distribution Industry....Pages 325-343
A Parallel Hybrid Implementation Using Genetic Algorithms, GRASP and Reinforcement Learning for the Salesman Traveling Problem....Pages 345-369
An Evolutionary Approach for the TSP and the TSP with Backhauls....Pages 371-396
Towards Efficient Multi-objective Genetic Takagi-Sugeno Fuzzy Systems for High Dimensional Problems....Pages 397-422
Evolutionary Algorithms for the Multi Criterion Minimum Spanning Tree Problem....Pages 423-452
Loss-Based Estimation with Evolutionary Algorithms and Cross-Validation....Pages 453-484
Front Matter....Pages 485-485
Particle Swarm Optimisation Aided MIMO Transceiver Designs....Pages 487-511
Optimal Design of a Common Rail Diesel Engine Piston....Pages 513-541
Front Matter....Pages 485-485
Robust Preliminary Space Mission Design under Uncertainty....Pages 543-570
Progressive Design Methodology for Design of Engineering Systems....Pages 571-607
Reliable Network Design Using Hybrid Genetic Algorithm Based on Multi-Ring Encoding....Pages 609-635
Isolated Word Analysis Using Biologically-Based Neural Networks....Pages 637-670
A Distributed Evolutionary Approach to Subtraction Radiography....Pages 671-700
Speeding-Up Expensive Evaluations in High-Level Synthesis Using Solution Modeling and Fitness Inheritance....Pages 701-723
Back Matter....Pages -
