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130626 ||| eng |
| 020 |
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|a 9781846281327
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| 100 |
1 |
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|a Tan, Kay Chen
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| 245 |
0 |
0 |
|a Multiobjective Evolutionary Algorithms and Applications
|h Elektronische Ressource
|c by Kay Chen Tan, Eik Fun Khor, Tong Heng Lee
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| 250 |
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|a 1st ed. 2005
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| 260 |
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|a London
|b Springer London
|c 2005, 2005
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| 300 |
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|a X, 296 p
|b online resource
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| 505 |
0 |
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|a Review of MOEAs -- Conceptual Framework and Distribution Preservation Mechanisms for MOEAs -- Decision Supports and Advanced Features for MOEAs -- Dynamic Population Size and Local Exploration for MOEAs -- A Distributed Cooperative Coevolutionary Multiobjective Algorithm -- Learning the Search Range in Dynamic Environments -- Performance Assessment and Comparison of MOEAs -- A Multiobjective Evolutionary Algorithm Toolbox -- Evolutionary Computer-Aided Control System Design -- Evolutionary Design Automation of Multivariable QFT Control System -- Evolutionary Design of HDD Servo Control System -- Evolutionary Scheduling — VRPTW -- Evolutionary Scheduling — TTVRP.
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| 653 |
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|a Computer science
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| 653 |
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|a Algorithms
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| 653 |
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|a Application software
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| 653 |
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|a Computer Application in Administrative Data Processing
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| 653 |
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|a Computer and Information Systems Applications
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| 653 |
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|a Information technology / Management
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| 653 |
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|a Theory of Computation
|
| 700 |
1 |
|
|a Khor, Eik Fun
|e [author]
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| 700 |
1 |
|
|a Lee, Tong Heng
|e [author]
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
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|b Springer
|a Springer eBooks 2005-
|
| 490 |
0 |
|
|a Advanced Information and Knowledge Processing
|
| 028 |
5 |
0 |
|a 10.1007/1-84628-132-6
|
| 856 |
4 |
0 |
|u https://doi.org/10.1007/1-84628-132-6?nosfx=y
|x Verlag
|3 Volltext
|
| 082 |
0 |
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|a 004.0151
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| 520 |
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|a Multiobjective Evolutionary Algorithms and Applications provides comprehensive treatment on the design of multiobjective evolutionary algorithms and their applications in domains covering areas such as control and scheduling. Emphasizing both the theoretical developments and the practical implementation of multiobjective evolutionary algorithms, a profound mathematical knowledge is not required. Written for a wide readership, engineers, researchers, senior undergraduates and graduate students interested in the field of evolutionary algorithms and multiobjective optimization with some basic knowledge of evolutionary computation will find this book a useful addition to their book case
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