Handbook of Approximation Algorithms and Metaheuristics, Second Edition, Gonzalez, Teofilo F.
Автор: Gendreau Название: Handbook of Metaheuristics ISBN: 331991085X ISBN-13(EAN): 9783319910857 Издательство: Springer Рейтинг: Цена: 20124.00 р. 25155.00-20% Наличие на складе: Есть (1 шт.) Описание: Metaheuristics have grown into one of the most prominent areas of operations research. This update of a trailblazing volume examines the latest developments in the field.
Автор: Gonzalez, Teofilo F. Название: Handbook of Approximation Algorithms and Metaheuristics ISBN: 0367571587 ISBN-13(EAN): 9780367571580 Издательство: Taylor&Francis Рейтинг: Цена: 6889.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Gonzalez, Teofilo F. Название: Handbook of Approximation Algorithms and Metaheuristics ISBN: 0367571595 ISBN-13(EAN): 9780367571597 Издательство: Taylor&Francis Рейтинг: Цена: 6889.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This handbook reflects the tremendous growth in the field, over the past two decades. Through contributions from leading experts, this handbook provides a comprehensive introduction to the underlying theory and methodologies, as well as the various applications of approximation algorithms and metaheuristics.
Автор: de Sourav, Dey Sandip, Bhattacharyya Siddhartha Название: Recent Advances in Hybrid Metaheuristics for Data Clustering ISBN: 1119551595 ISBN-13(EAN): 9781119551591 Издательство: Wiley Рейтинг: Цена: 16624.00 р. Наличие на складе: Поставка под заказ.
Описание:
An authoritative guide to an in-depth analysis of various state-of-the-art data clustering approaches using a range of computational intelligence techniques
Recent Advances in Hybrid Metaheuristics for Data Clustering offers a guide to the fundamentals of various metaheuristics and their application to data clustering. Metaheuristics are designed to tackle complex clustering problems where classical clustering algorithms have failed to be either effective or efficient. The authors--noted experts on the topic--provide a text that can aid in the design and development of hybrid metaheuristics to be applied to data clustering.
The book includes performance analysis of the hybrid metaheuristics in relationship to their conventional counterparts. In addition to providing a review of data clustering, the authors include in-depth analysis of different optimization algorithms. The text offers a step-by-step guide in the build-up of hybrid metaheuristics and to enhance comprehension. In addition, the book contains a range of real-life case studies and their applications. This important text:
Includes performance analysis of the hybrid metaheuristics as related to their conventional counterparts
Offers an in-depth analysis of a range of optimization algorithms
Highlights a review of data clustering
Contains a detailed overview of different standard metaheuristics in current use
Presents a step-by-step guide to the build-up of hybrid metaheuristics
Offers real-life case studies and applications
Written for researchers, students and academics in computer science, mathematics, and engineering, Recent Advances in Hybrid Metaheuristics for Data Clustering provides a text that explores the current data clustering approaches using a range of computational intelligence techniques.
Описание: This book constitutes the refereed proceedings of the Second Symposium on Machine Learning and Metaheuristics Algorithms, and Applications, SoMMA 2020, held in Chennai, India, in October 2020. The 12 full papers and 7 short papers presented in this volume were thoroughly reviewed and selected from 40 qualified submissions.
Автор: Blum Christian, Raidl Gьnther R. Название: Hybrid Metaheuristics: Powerful Tools for Optimization ISBN: 3319809075 ISBN-13(EAN): 9783319809076 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Christian Blum; G?nther R. Raidl Название: Hybrid Metaheuristics ISBN: 3319308823 ISBN-13(EAN): 9783319308821 Издательство: Springer Рейтинг: Цена: 10760.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Fouad Bennis; Rajib Kumar Bhattacharjya Название: Nature-Inspired Methods for Metaheuristics Optimization ISBN: 3030264572 ISBN-13(EAN): 9783030264574 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This book gathers together a set of chapters covering recent development in optimization methods that are inspired by nature. The first group of chapters describes in detail different meta-heuristic algorithms, and shows their applicability using some test or real-world problems. The second part of the book is especially focused on advanced applications and case studies. They span different engineering fields, including mechanical, electrical and civil engineering, and earth/environmental science, and covers topics such as robotics, water management, process optimization, among others. The book covers both basic concepts and advanced issues, offering a timely introduction to nature-inspired optimization method for newcomers and students, and a source of inspiration as well as important practical insights to engineers and researchers.
Описание: This book constitutes the refereed proceedings of the First Symposium on Machine Learning and Metaheuristics Algorithms, and Applications, held in Trivandrum, India, in December 2019. The 17 full papers and 6 short papers presented in this volume were thoroughly reviewed and selected from 53 qualified submissions.
Описание: This book explores new alternative metaheuristic developments that have proved to be effective in their application to several complex problems.
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