A New Meta-heuristic Optimization Algorithm Based on the String Theory Paradigm from Physics

This book proposes a new metaheuristic based on String Theory from Physics to generate new potential solutions in optimization problems, improving the results in solving these problems. It is presented in three case studies: optimization of traditional benchmark mathematical functions, optimization of benchmark functions of the CEC 2015 Competition, and optimization of a fuzzy inference system for finding the optimal design of a fuzzy controller for an autonomous mobile robot. Statistical tests are used to validate the performance of the proposed method.

Format: Paperback / softback
Length: 71 pages
Publication date: 19 August 2021
Publisher: Springer Nature Switzerland AG

This comprehensive book delves into the realms of nature-inspired algorithms, optimization problems, and fuzzy logic. Within its pages, a novel metaheuristic rooted in String Theory from Physics is presented, offering a fresh approach to generating potential solutions for optimization challenges. The primary objective of this endeavor is to explore innovative avenues that can enhance the outcomes in solving these complex problems.

We present the results of our proposed method across a diverse range of study cases. The first case involves the optimization of traditional benchmark mathematical functions, serving as a foundation for our exploration. The second case showcases the optimization of benchmark functions from the CEC 2015 Competition, highlighting our ability to tackle challenging real-world optimization problems. Additionally, we present results from the CEC 2017 Competition on Constrained Real-Parameter Optimization, which involves problems characterized by constraints that significantly alter the search space, making them more difficult to solve.

In the third case, we focus on the optimization of a fuzzy inference system, specifically aimed at finding the optimal design of a fuzzy controller for an autonomous mobile robot. To validate the performance of our proposed method, statistical tests are conducted in all study cases.

In conclusion, this book holds immense appeal to a broad audience, spanning from engineering and science graduate students to researchers and professors in computational intelligence, metaheuristics, optimization, robotics, and control. Its comprehensive coverage and innovative insights make it a valuable resource for advancing knowledge and understanding in these fields.

Weight: 142g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030822873
Edition number: 1st ed. 2022