Evolutionary Computation in Practice [electronic resource] / edited by Tina Yu, Lawrence Davis, Cem Baydar, Rajkumar Roy.

By: Yu, Tina [editor.]Contributor(s): Davis, Lawrence [editor.] | Baydar, Cem [editor.] | Roy, Rajkumar [editor.] | SpringerLink (Online service)Material type: TextTextLanguage: English Series: Studies in Computational Intelligence: 88Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008Description: XIV, 322 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783540757719Subject(s): Engineering | Artificial intelligence | Engineering mathematics | Engineering | Appl.Mathematics/Computational Methods of Engineering | Artificial Intelligence (incl. Robotics)Additional physical formats: Printed edition:: No titleDDC classification: 519 LOC classification: TA329-348TA640-643Online resources: Click here to access online
Contents:
An Introduction to Evolutionary Computation in Practice -- Design for Product Embedded Disassembly -- Multi-Level Decomposition for Tractability in Structural Design Optimization -- Representing the Change - Free Form Deformation for Evolutionary Design Optimization -- Evolving Microstructured Optical Fibres -- Making Interactive Evolutionary Graphic Design Practical -- Optimization of Store Performance Using Personalized Pricing -- A Computational Intelligence Approach to Railway Track Intervention Planning -- A Co-Evolutionary Fuzzy System for Reservoir Well Logs Interpretation -- Resource Scheduling with Permutation Based Representations: Three Applications -- Evolutionary Computation in the Chemical Industry -- Technology Transfer: Academia to Industry -- A Survey of Practitioners of Evolutionary Computation -- Evolutionary Computation Applications: Twelve Lessons Learned -- Evolutionary Computation at American Air Liquide.
In: Springer eBooksSummary: This book is loaded with examples in which computer scientists and engineers have used evolutionary computation—programs that mimic natural evolution—to solve real problems. They aren’t abstract, mathematically intensive papers, but accounts of solving important problems, including tips from the authors on how to avoid common pitfalls, maximize the effectiveness and efficiency of the search process, and many other practical suggestions. Some of the authors have already won "Humies"—Human Competitive Results Awards—for the work described in this book. I highly recommend it as a highly concentrated source of good problem-solving approaches that are applicable to many real-world problems. --Erik Goodman, Vice President, Red Cedar Technology, Inc.; Professor, Electrical & Computer Engineering, Michigan State University; and Founding Chair, ACM SIGEVO, the Special Interest Group on Genetic and Evolutionary Computation of the Association for Computing Machinery
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An Introduction to Evolutionary Computation in Practice -- Design for Product Embedded Disassembly -- Multi-Level Decomposition for Tractability in Structural Design Optimization -- Representing the Change - Free Form Deformation for Evolutionary Design Optimization -- Evolving Microstructured Optical Fibres -- Making Interactive Evolutionary Graphic Design Practical -- Optimization of Store Performance Using Personalized Pricing -- A Computational Intelligence Approach to Railway Track Intervention Planning -- A Co-Evolutionary Fuzzy System for Reservoir Well Logs Interpretation -- Resource Scheduling with Permutation Based Representations: Three Applications -- Evolutionary Computation in the Chemical Industry -- Technology Transfer: Academia to Industry -- A Survey of Practitioners of Evolutionary Computation -- Evolutionary Computation Applications: Twelve Lessons Learned -- Evolutionary Computation at American Air Liquide.

This book is loaded with examples in which computer scientists and engineers have used evolutionary computation—programs that mimic natural evolution—to solve real problems. They aren’t abstract, mathematically intensive papers, but accounts of solving important problems, including tips from the authors on how to avoid common pitfalls, maximize the effectiveness and efficiency of the search process, and many other practical suggestions. Some of the authors have already won "Humies"—Human Competitive Results Awards—for the work described in this book. I highly recommend it as a highly concentrated source of good problem-solving approaches that are applicable to many real-world problems. --Erik Goodman, Vice President, Red Cedar Technology, Inc.; Professor, Electrical & Computer Engineering, Michigan State University; and Founding Chair, ACM SIGEVO, the Special Interest Group on Genetic and Evolutionary Computation of the Association for Computing Machinery

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