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Advances in Metaheuristics


About the Series

This series delves into the topic of Metaheuristics and explores advancements in the area that will appeal to students, researchers, and professionals.

If you are interested in writing or editing a book for the series or would like more information, please contact Talitha Duncan-Todd, [email protected], or contact one of the Series Editors: Patrick Siarry at [email protected] and Anand Kulkarni at [email protected].

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Handbook of Moth-Flame Optimization Algorithm Variants, Hybrids, Improvements, and Applications

Handbook of Moth-Flame Optimization Algorithm: Variants, Hybrids, Improvements, and Applications

1st Edition

Forthcoming

Edited By Seyedali Mirjalili
September 20, 2022

Moth-Flame Optimization algorithm is an emerging meta-heuristic and has been widely used in both science and industry. Solving optimization problem using this algorithm requires addressing a number of challenges including multiple objectives, constraints, binary decision variables, large-scale ...

Hybrid Genetic Optimization for IC Chips Thermal Control With MATLAB® Applications

Hybrid Genetic Optimization for IC Chips Thermal Control: With MATLAB® Applications

1st Edition

Forthcoming

By Mathew V. K., Tapano Kumar Hotta
June 07, 2022

The continuous miniaturization of integrated circuit (IC) chips and the increase in the sleekness of the design of electronic components have led to the monumental rise of volumetric heat generation in electronic components. Hybrid Genetic Optimization for IC Chips Thermal Control: With MATLAB® ...

Constraint Handling in Cohort Intelligence Algorithm

Constraint Handling in Cohort Intelligence Algorithm

1st Edition

By Ishaan R. Kale, Anand J. Kulkarni
December 27, 2021

Mechanical Engineering domain problems are generally complex, consisting of different design variables and constraints. These problems may not be solved using gradient-based optimization techniques. The stochastic nature-inspired optimization techniques have been proposed in this book to ...

Metaheuristic Algorithms in Industry 4.0

Metaheuristic Algorithms in Industry 4.0

1st Edition

Edited By Pritesh Shah, Ravi Sekhar, Anand J. Kulkarni, Patrick Siarry
September 29, 2021

Due to increasing industry 4.0 practices, massive industrial process data is now available for researchers for modelling and optimization. Artificial Intelligence methods can be applied to the ever-increasing process data to achieve robust control against foreseen and unforeseen system fluctuations...

Handbook of AI-based Metaheuristics

Handbook of AI-based Metaheuristics

1st Edition

Edited By Anand J. Kulkarni, Patrick Siarry
September 02, 2021

At the heart of the optimization domain are mathematical modeling of the problem and the solution methodologies. The problems are becoming larger and with growing complexity. Such problems are becoming cumbersome when handled by traditional optimization methods. This has motivated researchers to ...

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