Genetic Algorithms and Fuzzy Multiobjective Optimization

Name: Genetic Algorithms and Fuzzy Multiobjective Optimization
Brand: Springer
SKU: 9780792374527
Price: 59155 HUF
Availability: InStock

Szerző: Masatoshi Sakawa

Nyelv:

Kötés: Kemény kötésű

Kiadó: Springer

Elérhetőség: Beszállítói készleten

Küldés 10-13 napon belül

59 155 Ft

Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together w...

Információk a könyvről

Szerző

Masatoshi Sakawa

Nyelv

Angol

Kötés

Könyv - Kemény kötésű

Kiadva

2001

oldal

288

EAN

9780792374527

ISBN

0792374525

Enbook ID

01397060

Kiadó

Springer

Súly

1330

Méretek

155 x 235 x 21

Teljes leírás

Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together with several significant monographs and books have been published on this methodology. As a result, genetic algorithms have made a major contribution to optimization, adaptation, and learning in a wide variety of unexpected fields. Over the years, many excellent books in genetic algorithm optimization have been published; however, they focus mainly on single-objective discrete or other hard optimization problems under certainty. There appears to be no book that is designed to present genetic algorithms for solving not only single-objective but also fuzzy and multiobjective optimization problems in a unified way. Genetic Algorithms And Fuzzy Multiobjective Optimization introduces the latest advances in the field of genetic algorithm optimization for 0-1 programming, integer programming, nonconvex programming, and job-shop scheduling problems under multiobjectiveness and fuzziness. In addition, the book treats a wide range of actual real world applications. The theoretical material and applications place special stress on interactive decision-making aspects of fuzzy multiobjective optimization for human-centered systems in most realistic situations when dealing with fuzziness. The intended readers of this book are senior undergraduate students, graduate students, researchers, and practitioners in the fields of operations research, computer science, industrial engineering, management science, systems engineering, and other engineering disciplines that deal with the subjects of multiobjective programming for discrete or other hard optimization problems under fuzziness. Real world research applications are used throughout the book to illustrate the presentation. These applications are drawn from complex problems. Examples include flexible scheduling in a machine center, operation planning of district heating and cooling plants, and coal purchase planning in an actual electric power plant.

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Genetic Algorithms and Fuzzy Multiobjective Optimization

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