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Comparative analysis of various Evolutionary Algorithms: Past three decades.

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Titel: Comparative analysis of various Evolutionary Algorithms: Past three decades.
Autoren: Srikumar, A., Pande, Sagar Dhanraj
Quelle: EAI Endorsed Transactions on Scalable Information Systems; 2024, Vol. 11 Issue 4, p1-12, 12p
Schlagwörter: TREND analysis, COMPARATIVE studies, DATA mining, GENETIC algorithms, PROBLEM solving
Abstract: INTRODUCTION: The Evolutionary algorithms created back in 1953, have gone through various phases of development over the years. It has been put to use to solve various problems in different domains including complex problems such as the infamous problem of Travelling Salesperson (TSP). OBJECTIVES: The main objective of this research is to find out the advancements in Evolutionary algorithms and to check whether it is still relevant in 2023. METHODS: To give an overview of the related concepts, subdomains, pros, and cons, the historical and recent developments are discussed and critiqued to provide insights into the results and a better conception of the trends in the domain. RESULTS: For a better perception of the development of evolutionary algorithms over the years, decade-wise trend analysis has been done for the past three decades. CONCLUSION: Scope of research in the domain is ever expanding and to name a few EAs for Data mining, Hybrid EAs are still under development. [ABSTRACT FROM AUTHOR]
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Datenbank: Complementary Index
Beschreibung
Abstract:INTRODUCTION: The Evolutionary algorithms created back in 1953, have gone through various phases of development over the years. It has been put to use to solve various problems in different domains including complex problems such as the infamous problem of Travelling Salesperson (TSP). OBJECTIVES: The main objective of this research is to find out the advancements in Evolutionary algorithms and to check whether it is still relevant in 2023. METHODS: To give an overview of the related concepts, subdomains, pros, and cons, the historical and recent developments are discussed and critiqued to provide insights into the results and a better conception of the trends in the domain. RESULTS: For a better perception of the development of evolutionary algorithms over the years, decade-wise trend analysis has been done for the past three decades. CONCLUSION: Scope of research in the domain is ever expanding and to name a few EAs for Data mining, Hybrid EAs are still under development. [ABSTRACT FROM AUTHOR]
ISSN:20329407
DOI:10.4108/eetsis.4356