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Multiobjective Optimization Methodology - A Jumping Gene Approach (Hardcover) Loot Price: R3,799
Discovery Miles 37 990
You Save: R710 (16%)
Multiobjective Optimization Methodology - A Jumping Gene Approach (Hardcover): K.S. Tang, T. M. Chan, R. J. Yin, K.F. Man

Multiobjective Optimization Methodology - A Jumping Gene Approach (Hardcover)

K.S. Tang, T. M. Chan, R. J. Yin, K.F. Man

Series: Industrial Electronics

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List price R4,509 Loot Price R3,799 Discovery Miles 37 990 | Repayment Terms: R356 pm x 12* You Save R710 (16%)

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The first book to focus on jumping genes outside bioscience and medicine, Multiobjective Optimization Methodology: A Jumping Gene Approach introduces jumping gene algorithms designed to supply adequate, viable solutions to multiobjective problems quickly and with low computational cost. Better Convergence and a Wider Spread of Nondominated Solutions The book begins with a thorough review of state-of-the-art multiobjective optimization techniques. For readers who may not be familiar with the bioscience behind the jumping gene, it then outlines the basic biological gene transposition process and explains the translation of the copy-and-paste and cut-and-paste operations into a computable language. To justify the scientific standing of the jumping genes algorithms, the book provides rigorous mathematical derivations of the jumping genes operations based on schema theory. It also discusses a number of convergence and diversity performance metrics for measuring the usefulness of the algorithms. Practical Applications of Jumping Gene Algorithms Three practical engineering applications showcase the effectiveness of the jumping gene algorithms in terms of the crucial trade-off between convergence and diversity. The examples deal with the placement of radio-to-fiber repeaters in wireless local-loop systems, the management of resources in WCDMA systems, and the placement of base stations in wireless local-area networks. Offering insight into multiobjective optimization, the authors show how jumping gene algorithms are a useful addition to existing evolutionary algorithms, particularly to obtain quick convergence solutions and solutions to outliers.

General

Imprint: Crc Press
Country of origin: United States
Series: Industrial Electronics
Release date: May 2012
First published: 2012
Authors: K.S. Tang • T. M. Chan • R. J. Yin • K.F. Man
Dimensions: 234 x 156 x 22mm (L x W x T)
Format: Hardcover
Pages: 279
ISBN-13: 978-1-4398-9919-9
Categories: Books > Professional & Technical > Technology: general issues > Technical design > General
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LSN: 1-4398-9919-3
Barcode: 9781439899199

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