Prof. G. K. Chadha Library

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Sine cosine algorithm for optimization / Jagdish Chand Bansal, Prathu Bajpai, Anjali Rawat, Atulya K. Nagar.

By: Bansal, Jagdish Chand [author.].
Contributor(s): Bajpai, Prathu [author.] | Rawat, Anjali [author.] | Nagar, Atulya K [author.].
Material type: TextTextSeries: SpringerBriefs in applied sciences and technologyComputational intelligence: Publisher: Singapore : Springer, 2023Description: x, 108 pages : illustrations (chiefly color) ; 24 cm.ISBN: 9789811997211; 9811997225; 9789811997228.Subject(s): Metaheuristics | Mathematical optimization | Computer programmingDDC classification: 005.13
Contents:
Introduction -- Sine Cosine Algorithm -- Sine Cosine Algorithm for Multi-Objective Optimization -- Sine Cosine Algorithm for Discrete Optimization Problems -- Advancements in the Sine Cosine Algorithm -- Conclusion and Further Research Directions.
Summary: This open access book serves as a compact source of information on sine cosine algorithm (SCA) and a foundation for developing and advancing SCA and its applications. SCA is an easy, user-friendly, and strong candidate in the field of metaheuristics algorithms. Despite being a relatively new metaheuristic algorithm, it has achieved widespread acceptance among researchers due to its easy implementation and robust optimization capabilities. Its effectiveness and advantages have been demonstrated in various applications ranging from machine learning, engineering design, and wireless sensor network to environmental modeling. The book provides a comprehensive account of the SCA, including details of the underlying ideas, the modified versions, various applications, and a working MATLAB code for the basic SCA.
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Books Books Prof. G. K. Chadha Library

South Asian University

General Stacks 		005.13 B2196s (Browse shelf) Available BKD0000692
Total holds: 0

Includes bibliographical references and index.

Introduction -- Sine Cosine Algorithm -- Sine Cosine Algorithm for Multi-Objective Optimization -- Sine Cosine Algorithm for Discrete Optimization Problems -- Advancements in the Sine Cosine Algorithm -- Conclusion and Further Research Directions.

This open access book serves as a compact source of information on sine cosine algorithm (SCA) and a foundation for developing and advancing SCA and its applications. SCA is an easy, user-friendly, and strong candidate in the field of metaheuristics algorithms. Despite being a relatively new metaheuristic algorithm, it has achieved widespread acceptance among researchers due to its easy implementation and robust optimization capabilities. Its effectiveness and advantages have been demonstrated in various applications ranging from machine learning, engineering design, and wireless sensor network to environmental modeling. The book provides a comprehensive account of the SCA, including details of the underlying ideas, the modified versions, various applications, and a working MATLAB code for the basic SCA.

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