Design of Modern Heuristics [recurso electrónico] : Principles and Application / by Franz Rothlauf.

Por: Rothlauf, Franz [author.]Colaborador(es): SpringerLink (Online service)Tipo de material: TextoTextoSeries Natural Computing SeriesEditor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011Descripción: XI, 267 p. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783540729624Tema(s): Computer science | Artificial intelligence | Mathematical optimization | Engineering | Management information systems | Computer Science | Artificial Intelligence (incl. Robotics) | Optimization | Computational Intelligence | Business Information SystemsFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 006.3 Clasificación LoC:Q334-342TJ210.2-211.495Recursos en línea: Libro electrónicoTexto
Contenidos:
Chap. 1 -- Introduction -- Part I -- Fundamentals -- Chap. 2 -- Optimization Problems -- Chap. 3 -- Optimization Methods -- Part II -- Modern Heuristics -- Chap. 4 -- Design Elements -- Chap. 5 -- Search Strategies -- Chap. 6 -- Design Principles -- Part III Case Studies -- Chap. 7 -- High Locality Representations for Automated Programming -- Chap. 8.-Biased Modern Heuristics for the OCST Problem -- Chap. 9.-Summary -- References -- Nomenclature -- Glossary -- Index.
En: Springer eBooksResumen: Most textbooks on modern heuristics provide the reader with detailed descriptions of the functionality of single examples like genetic algorithms, genetic programming, tabu search, simulated annealing, and others, but fail to teach the underlying concepts behind these different approaches. The author takes a different approach in this textbook by focusing on the users' needs and answering three fundamental questions: First, he tells us which problems modern heuristics are expected to perform well on, and which should be left to traditional optimization methods. Second, he teaches us to systematically design the "right" modern heuristic for a particular problem by providing a coherent view on design elements and working principles. Third, he shows how we can make use of problem-specific knowledge for the design of efficient and effective modern heuristics that solve not only small toy problems but also perform well on large real-world problems. This book is written in an easy-to-read style and it is aimed at students and practitioners in computer science, operations research and information systems who want to understand modern heuristics and are interested in a guide to their systematic design and use.
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Existencias
Tipo de ítem Biblioteca actual Colección Signatura Copia número Estado Fecha de vencimiento Código de barras
Libro Electrónico Biblioteca Electrónica
Colección de Libros Electrónicos Q334 -342 (Browse shelf(Abre debajo)) 1 No para préstamo 373195-2001

Chap. 1 -- Introduction -- Part I -- Fundamentals -- Chap. 2 -- Optimization Problems -- Chap. 3 -- Optimization Methods -- Part II -- Modern Heuristics -- Chap. 4 -- Design Elements -- Chap. 5 -- Search Strategies -- Chap. 6 -- Design Principles -- Part III Case Studies -- Chap. 7 -- High Locality Representations for Automated Programming -- Chap. 8.-Biased Modern Heuristics for the OCST Problem -- Chap. 9.-Summary -- References -- Nomenclature -- Glossary -- Index.

Most textbooks on modern heuristics provide the reader with detailed descriptions of the functionality of single examples like genetic algorithms, genetic programming, tabu search, simulated annealing, and others, but fail to teach the underlying concepts behind these different approaches. The author takes a different approach in this textbook by focusing on the users' needs and answering three fundamental questions: First, he tells us which problems modern heuristics are expected to perform well on, and which should be left to traditional optimization methods. Second, he teaches us to systematically design the "right" modern heuristic for a particular problem by providing a coherent view on design elements and working principles. Third, he shows how we can make use of problem-specific knowledge for the design of efficient and effective modern heuristics that solve not only small toy problems but also perform well on large real-world problems. This book is written in an easy-to-read style and it is aimed at students and practitioners in computer science, operations research and information systems who want to understand modern heuristics and are interested in a guide to their systematic design and use.

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