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  • © 2010

Computational Intelligence in Expensive Optimization Problems

  • First book to introduce the emerging field of computational intelligence in expensive optimization problems
  • Provides both theoretical treatments and real-world insights gained by experience in computational intelligence in expensive optimization problems

Part of the book series: Adaptation, Learning, and Optimization (ALO, volume 2)

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Table of contents (26 chapters)

  1. Front Matter

  2. Techniques for Resource-Intensive Problems

    1. Front Matter

      Pages 1-1
    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
      Pages 29-59
    3. Kriging Is Well-Suited to Parallelize Optimization

      • David Ginsbourger, Rodolphe Le Riche, Laurent Carraro
      Pages 131-162
    4. Analysis of Approximation-Based Memetic Algorithms for Engineering Optimization

      • Frederico Gadelha Guimarães, David Alister Lowther, Jaime Arturo Ramírez
      Pages 163-191
    5. Multi-objective Model Predictive Control Using Computational Intelligence

      • Hirotaka Nakayama, Yeboon Yun, Masakazu Shirakawa
      Pages 249-264
  3. Techniques for High-Dimensional Problems

    1. Front Matter

      Pages 295-295
    2. Differential Evolution with Scale Factor Local Search for Large Scale Problems

      • Andrea Caponio, Anna V. Kononova, Ferrante Neri
      Pages 297-323
    3. A Parallel Hybrid Implementation Using Genetic Algorithms, GRASP and Reinforcement Learning for the Salesman Traveling Problem

      • João Paulo Queiroz dos Santos, Francisco Chagas de Lima Júnior, Rafael Marrocos Magalhães, Jorge Dantas de Melo, Adrião Duarte Doria Neto
      Pages 345-369
    4. An Evolutionary Approach for the TSP and the TSP with Backhauls

      • Haldun Süral, Nur Evin Özdemirel, Ýlter Önder, Meltem Sönmez Turan
      Pages 371-396
    5. Towards Efficient Multi-objective Genetic Takagi-Sugeno Fuzzy Systems for High Dimensional Problems

      • Marco Cococcioni, Beatrice Lazzerini, Francesco Marcelloni
      Pages 397-422
    6. Evolutionary Algorithms for the Multi Criterion Minimum Spanning Tree Problem

      • Madeleine Davis-Moradkhan, Will Browne
      Pages 423-452

About this book

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.

Editors and Affiliations

  • Department of Mechanical Engineering and Science-Faculty of Engineering, Kyoto University, Kyoto, Japan

    Yoel Tenne

  • Advanced Technology Centre, Rolls-Royce Singapore Pte Ltd, Singapore

    Chi-Keong Goh

Bibliographic Information

Buy it now

Buying options

eBook USD 259.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 329.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access