Multiobjective Evolutionary Algorithms and Applications (Advanced Information and Knowledge Processing) - Info and Reading Options
By K. C. Tan
"Multiobjective Evolutionary Algorithms and Applications (Advanced Information and Knowledge Processing)" is published by Springer in May 4, 2005, it has 295 pages and the language of the book is English.
“Multiobjective Evolutionary Algorithms and Applications (Advanced Information and Knowledge Processing)” Metadata:
- Title: ➤ Multiobjective Evolutionary Algorithms and Applications (Advanced Information and Knowledge Processing)
- Author: K. C. Tan
- Language: English
- Number of Pages: 295
- Publisher: Springer
- Publish Date: May 4, 2005
“Multiobjective Evolutionary Algorithms and Applications (Advanced Information and Knowledge Processing)” Subjects and Themes:
- Subjects: ➤ Computer algorithms - Evolutionary computation - Mathematical optimization - Evolutionary computing - Computer science - Computer software - Information systems - Algorithm Analysis and Problem Complexity - Computer Appl. in Administrative Data Processing - Information Systems Applications (incl.Internet)
Edition Specifications:
- Format: Hardcover
- Weight: 1.2 pounds
- Dimensions: 9.6 x 6.4 x 0.9 inches
Edition Identifiers:
- The Open Library ID: OL8974442M - OL16960833W
- Online Computer Library Center (OCLC) ID: 56641555
- Library of Congress Control Number (LCCN): 2005432819
- ISBN-13: 9781852338367
- ISBN-10: 1852338369
- All ISBNs: 1852338369 - 9781852338367
AI-generated Review of “Multiobjective Evolutionary Algorithms and Applications (Advanced Information and Knowledge Processing)”:
"Multiobjective Evolutionary Algorithms and Applications (Advanced Information and Knowledge Processing)" Description:
The Open Library:
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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