Description

Book Synopsis
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.


Table of 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.

Sine Cosine Algorithm for Optimization

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    A Paperback / softback by Jagdish Chand Bansal, Prathu Bajpai, Anjali Rawat

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      Book details

      Publisher Springer Verlag, Singapore
      Published 31 January 2023
      ISBN-13 9789811997211
      978-9811997211
      ISBN-10 9811997217
      Also in:
      Artificial intelligence (AI) Numerical analysis Optimization

      Description

      Book Synopsis
      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.


      Table of 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.

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