Isbn: 9781138072558 - multiobjective optimization methodology: a jumping gene approach (industrial electronics) (14 resultados)

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Condición: New.

Paperback. Condición: new. Paperback. 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 SolutionsThe 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 AlgorithmsThree 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condición: New. pp. 279.

Condición: New. pp. 279.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New. pp. 279.

Condición: New. 2018. 1st Edition. Paperback. . . . . .

Paperback. Condición: Brand New. reprint edition. 279 pages. 9.21x6.14x0.59 inches. In Stock.

Condición: New. 2018. 1st Edition. Paperback. . . . . . Books ship from the US and Ireland.

Condición: New. Kit Sang Tang received his BSc from the University of Hong Kong in 1988 and his MSc and PhD from City University of Hong Kong in 1992 and 1996, respectively. He is currently an associate professor in the Department of Electronic Engineer.

Paperback. Condición: new. Paperback. 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 SolutionsThe 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 AlgorithmsThree 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

paperback. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.