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100301s2009 gw | s |||| 0|eng d |
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|a 9783540880516
|9 978-3-540-88051-6
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|a 10.1007/978-3-540-88051-6
|2 doi
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|a TA329-348
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|a TA640-643
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|a TBJ
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|a MAT003000
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|a 519
|2 23
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|a Goh, Chi-Keong.
|e editor.
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|a Multi-Objective Memetic Algorithms
|c edited by Chi-Keong Goh, Yew-Soon Ong, Kay Chen Tan.
|h [electronic resource] /
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| 264 |
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg,
|c 2009.
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| 300 |
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|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a text file
|b PDF
|2 rda
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| 490 |
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|a Studies in Computational Intelligence,
|v 171
|x 1860-949X ;
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| 505 |
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|a Part I Introduction Evolutionary Multi-Multi-Objective Optimization EMMOO -- Part II Knowledge Infused in Design of Problem-Specific Operators Solving Time-Tabling Problems using Evolutionary Algorithms and Heuristics Search -- Part III Knowledge Propagation through Cultural Evolution Risk and Cost Tradeoff In Economic Dispatch Including Wind Power Penetration Based on Multi-objective Memetic Particle Swarm Optimization -- Part IV Information Exploited for Local Improvement Combination of Genetic Algorithms and Evolution Strategies with Self-Adaptive Switching.
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|a The application of sophisticated evolutionary computing approaches for solving complex problems with multiple conflicting objectives in science and engineering have increased steadily in the recent years. Within this growing trend, Memetic algorithms are, perhaps, one of the most successful stories, having demonstrated better efficacy in dealing with multi-objective problems as compared to its conventional counterparts. Nonetheless, researchers are only beginning to realize the vast potential of multi-objective Memetic algorithm and there remain many open topics in its design. This book presents a very first comprehensive collection of works, written by leading researchers in the field, and reflects the current state-of-the-art in the theory and practice of multi-objective Memetic algorithms. "Multi-Objective Memetic algorithms" is organized for a wide readership and will be a valuable reference for engineers, researchers, senior undergraduates and graduate students who are interested in the areas of Memetic algorithms and multi-objective optimization.
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| 650 |
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|a Engineering.
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| 650 |
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|a Artificial intelligence.
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| 650 |
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|a Engineering mathematics.
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1 |
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|a Engineering.
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| 650 |
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|a Appl.Mathematics/Computational Methods of Engineering.
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| 650 |
2 |
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|a Artificial Intelligence (incl. Robotics).
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| 700 |
1 |
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|a Ong, Yew-Soon.
|e editor.
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| 700 |
1 |
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|a Tan, Kay Chen.
|e editor.
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| 710 |
2 |
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|a SpringerLink (Online service)
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|t Springer eBooks
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| 776 |
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8 |
|i Printed edition:
|z 9783540880509
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| 830 |
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|a Studies in Computational Intelligence,
|v 171
|x 1860-949X ;
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| 856 |
4 |
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|u https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-540-88051-6
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| 912 |
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|a ZDB-2-ENG
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| 950 |
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|a Engineering (Springer-11647)
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