Mutingi Grouping Genetic Algorithms 9783319443935

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Автор: Mutingi
Название: Grouping Genetic Algorithms
ISBN: 9783319443935
Издательство: Springer
Классификация:

Исследование операций

Организация производственных процессов

Алгоритмы и структуры данных

Искусственный интеллект

ISBN-10: 3319443933
Обложка/Формат: Hardback
Страницы: 243
Вес: 0.56 кг.
Дата издания: 2017
Серия: Studies in Computational Intelligence
Язык: English
Издание: 1st ed. 2017
Иллюстрации: 78 illustrations, black and white; xiv, 243 p. 78 illus.
Размер: 234 x 156 x 16
Читательская аудитория: Professional & vocational
Основная тема: Engineering
Подзаголовок: Advances and Applications
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
Описание: This book presents advances and innovations in grouping genetic algorithms, enriched with new and unique heuristic optimization techniques. These algorithms are specially designed for solving industrial grouping problems where system entities are to be partitioned or clustered into efficient groups according to a set of guiding decision criteria. Examples of such problems are: vehicle routing problems, team formation problems, timetabling problems, assembly line balancing, group maintenance planning, modular design, and task assignment. A wide range of industrial grouping problems, drawn from diverse fields such as logistics, supply chain management, project management, manufacturing systems, engineering design and healthcare, are presented. Typical complex industrial grouping problems, with multiple decision criteria and constraints, are clearly described using illustrative diagrams and formulations. The problems are mapped into a common group structure that can conveniently be used as an input scheme to specific variants of grouping genetic algorithms. Unique heuristic grouping techniques are developed to handle grouping problems efficiently and effectively. Illustrative examples and computational results are presented in tables and graphs to demonstrate the efficiency and effectiveness of the algorithms.Researchers, decision analysts, software developers, and graduate students from various disciplines will find this in-depth reader-friendly exposition of advances and applications of grouping genetic algorithms an interesting, informative and valuable resource.

Дополнительное описание: Part I: Introduction.- Exploring Grouping Problems in Industry.- Complicating Features in Grouping Problems.- Part II: Grouping Genetic Algorithms.- Crouping Genetic Algorithms.- Fuzzy Grouping Genetic Algorithms.- Research Applications.- Fleet Size and M

Grouping Genetic Algorithms, Mutingi