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A Literature Review and Critical Analysis of Metaheuristics Recently Developed
https://orcid.org/0000-0001-8074-4744
AbstractMetaheuristic algorithms have applicability in various fields where it is necessary to solve optimization problems. It has been a common practice in this field for several years to propose new algorithms that take inspiration from various natural and physical processes. The exponential increase of new algorithms is a controversial issue that several researchers have criticized. However, their efforts to point out multiple issues involved in these practices have been insufficient since the number of existing metaheuristics continues to increase yearly. To know the current state of this problem, this paper analyzes a sample of 111 recent studies where so-called new, hybrid, or improved optimization algorithms are proposed. Throughout the document, the topics reviewed will be addressed from a general perspective to their specific aspects. Among the study’s findings, it is observed that only 43% of the analyzed papers make some mention of the No Free Lunch (NFL) theorem, being this significant result ignored by most of the studies where new algorithms are presented. Of the analyzed studies, 65% present an improved version of some established algorithm, which reveals that the trend is no longer to propose metaheuristics based on new analogies. Additionally, a compilation of solutions found in engineering problems commonly used to verify the performance of state-of-the-art algorithms is presented. To demonstrate that algorithms with a low level of innovation can be erroneously considered as new frameworks for years, the metaheuristics known as Black Widow Optimization and Coral Reef Optimization are analyzed. The study of its components reveals that they do not have any innovation. Instead, they are just deficient mixtures of different evolutionary operators. This result applies by extension to their recently proposed improved versions.
A Literature Review and Critical Analysis of Metaheuristics Recently Developed
https://orcid.org/0000-0001-8074-4744
AbstractMetaheuristic algorithms have applicability in various fields where it is necessary to solve optimization problems. It has been a common practice in this field for several years to propose new algorithms that take inspiration from various natural and physical processes. The exponential increase of new algorithms is a controversial issue that several researchers have criticized. However, their efforts to point out multiple issues involved in these practices have been insufficient since the number of existing metaheuristics continues to increase yearly. To know the current state of this problem, this paper analyzes a sample of 111 recent studies where so-called new, hybrid, or improved optimization algorithms are proposed. Throughout the document, the topics reviewed will be addressed from a general perspective to their specific aspects. Among the study’s findings, it is observed that only 43% of the analyzed papers make some mention of the No Free Lunch (NFL) theorem, being this significant result ignored by most of the studies where new algorithms are presented. Of the analyzed studies, 65% present an improved version of some established algorithm, which reveals that the trend is no longer to propose metaheuristics based on new analogies. Additionally, a compilation of solutions found in engineering problems commonly used to verify the performance of state-of-the-art algorithms is presented. To demonstrate that algorithms with a low level of innovation can be erroneously considered as new frameworks for years, the metaheuristics known as Black Widow Optimization and Coral Reef Optimization are analyzed. The study of its components reveals that they do not have any innovation. Instead, they are just deficient mixtures of different evolutionary operators. This result applies by extension to their recently proposed improved versions.
A Literature Review and Critical Analysis of Metaheuristics Recently Developed
https://orcid.org/0000-0001-8074-4744
AbstractMetaheuristic algorithms have applicability in various fields where it is necessary to solve optimization problems. It has been a common practice in this field for several years to propose new algorithms that take inspiration from various natural and physical processes. The exponential increase of new algorithms is a controversial issue that several researchers have criticized. However, their efforts to point out multiple issues involved in these practices have been insufficient since the number of existing metaheuristics continues to increase yearly. To know the current state of this problem, this paper analyzes a sample of 111 recent studies where so-called new, hybrid, or improved optimization algorithms are proposed. Throughout the document, the topics reviewed will be addressed from a general perspective to their specific aspects. Among the study’s findings, it is observed that only 43% of the analyzed papers make some mention of the No Free Lunch (NFL) theorem, being this significant result ignored by most of the studies where new algorithms are presented. Of the analyzed studies, 65% present an improved version of some established algorithm, which reveals that the trend is no longer to propose metaheuristics based on new analogies. Additionally, a compilation of solutions found in engineering problems commonly used to verify the performance of state-of-the-art algorithms is presented. To demonstrate that algorithms with a low level of innovation can be erroneously considered as new frameworks for years, the metaheuristics known as Black Widow Optimization and Coral Reef Optimization are analyzed. The study of its components reveals that they do not have any innovation. Instead, they are just deficient mixtures of different evolutionary operators. This result applies by extension to their recently proposed improved versions.
A Literature Review and Critical Analysis of Metaheuristics Recently Developed
Arch Computat Methods Eng
Velasco, Luis (author) / Guerrero, Hector (author) / Hospitaler, Antonio (author)
Archives of Computational Methods in Engineering ; 31 ; 125-146
2024-01-01
Article (Journal)
Electronic Resource
English
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