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A new meta-heuristic optimization al...

Castillo, Oscar.

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A new meta-heuristic optimization algorithm based on the string theory paradigm from physics

Record Type:	Electronic resources : Monograph/item
Title/Author:	A new meta-heuristic optimization algorithm based on the string theory paradigm from physics/ by Oscar Castillo, Luis Rodriguez.
Author:	Castillo, Oscar.
other author:	Rodriguez, Luis.
Published:	Cham :Springer International Publishing : : 2022.,
Description:	viii, 71 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Literature Review -- String Theory Algorithm -- Simulation Results -- Conclusions.
Contained By:	Springer Nature eBook
Subject:	Metaheuristics. -
Online resource:	https://doi.org/10.1007/978-3-030-82288-0
ISBN:	9783030822880

A new meta-heuristic optimization algorithm based on the string theory paradigm from physics
Castillo, Oscar.

A new meta-heuristic optimization algorithm based on the string theory paradigm from physics[electronic resource] /by Oscar Castillo, Luis Rodriguez. - Cham :Springer International Publishing :2022. - viii, 71 p. :ill., digital ;24 cm. - SpringerBriefs in applied sciences and technology. Computational intelligence. - SpringerBriefs in applied sciences and technology.Computational intelligence..

Introduction -- Literature Review -- String Theory Algorithm -- Simulation Results -- Conclusions.

This book focuses on the fields of nature-inspired algorithms, optimization problems and fuzzy logic. In this book, a new metaheuristic based on String Theory from Physics is proposed. It is important to mention that we have proposed the new algorithm to generate new potential solutions in optimization problems in order to find new ways that could improve the results in solving these problems. We are presenting the results for the proposed method in different cases of study. The first case, is optimization of traditional benchmark mathematical functions. The second case, is the optimization of benchmark functions of the CEC 2015 Competition and we are also presenting results of the CEC 2017 Competition on Constrained Real-Parameter Optimization that are problems that contain the presence of constraints that alter the shape of the search space making them more difficult to solve. Finally, in the third case, we are presenting the optimization of a fuzzy inference system, specifically for finding the optimal design of a fuzzy controller for an autonomous mobile robot. It is important to mention that in all study cases we are presenting statistical tests in or-der to validate the performance of proposed method. In summary, we believe that this book will be of great interest to a wide audience, ranging from engineering and science graduate students, to researchers and professors in computational intelligence, metaheuristics, optimization, robotics and control.

ISBN: 9783030822880

Standard No.: 10.1007/978-3-030-82288-0doiSubjects--Topical Terms:

2206834
Metaheuristics.

LC Class. No.: QA76.9.A43 / C37 2022

Dewey Class. No.: 518.1

A new meta-heuristic optimization algorithm based on the string theory paradigm from physics
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490 1 $a SpringerBriefs in applied sciences and technology. Computational intelligence
505 0 $a Introduction -- Literature Review -- String Theory Algorithm -- Simulation Results -- Conclusions.
520 $a This book focuses on the fields of nature-inspired algorithms, optimization problems and fuzzy logic. In this book, a new metaheuristic based on String Theory from Physics is proposed. It is important to mention that we have proposed the new algorithm to generate new potential solutions in optimization problems in order to find new ways that could improve the results in solving these problems. We are presenting the results for the proposed method in different cases of study. The first case, is optimization of traditional benchmark mathematical functions. The second case, is the optimization of benchmark functions of the CEC 2015 Competition and we are also presenting results of the CEC 2017 Competition on Constrained Real-Parameter Optimization that are problems that contain the presence of constraints that alter the shape of the search space making them more difficult to solve. Finally, in the third case, we are presenting the optimization of a fuzzy inference system, specifically for finding the optimal design of a fuzzy controller for an autonomous mobile robot. It is important to mention that in all study cases we are presenting statistical tests in or-der to validate the performance of proposed method. In summary, we believe that this book will be of great interest to a wide audience, ranging from engineering and science graduate students, to researchers and professors in computational intelligence, metaheuristics, optimization, robotics and control.
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