Non-dominated sorting genetic algorithm

Seyedali Mirjalili; Jin Song Dong

doi:10.1007/978-3-030-24835-2_4

Non-dominated sorting genetic algorithm

Seyedali Mirjalili, Jin Song Dong

Artificial Intelligence Research and Optimization

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

4 Citations (Scopus)

Abstract

Evolutionary Algorithms mimic natural evolutionary process in nature. One of the most well-regarded evolutionary algorithms is Genetic Algorithm (GA) [1]. This algorithm has been inspired from the Drawin's theory of evolutionary. This theory states that natural organisms develop using the natural selection. Natural selection refers to the process of selecting and propagating the best genes from one generation to the next that helps the new generation to better survive, compete, and reproduce.

Original language	English
Title of host publication	SpringerBriefs in Applied Sciences and Technology
Publisher	Springer Verlag
Pages	37-45
Number of pages	9
DOIs	https://doi.org/10.1007/978-3-030-24835-2_4
Publication status	Published - 1 Jan 2020

Publication series

Name	SpringerBriefs in Applied Sciences and Technology
ISSN (Print)	2191-530X
ISSN (Electronic)	2191-5318

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/978-3-030-24835-2_4

Cite this

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abstract = "Evolutionary Algorithms mimic natural evolutionary process in nature. One of the most well-regarded evolutionary algorithms is Genetic Algorithm (GA) [1]. This algorithm has been inspired from the Drawin's theory of evolutionary. This theory states that natural organisms develop using the natural selection. Natural selection refers to the process of selecting and propagating the best genes from one generation to the next that helps the new generation to better survive, compete, and reproduce.",

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Non-dominated sorting genetic algorithm

Abstract

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UN SDGs

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