Genetic algorithm: Theory, literature review, and application in image reconstruction

Seyedali Mirjalili, Jin Song Dong, Ali Safa Sadiq, Hossam Faris

Research output: Chapter in Book/Report/Conference proceedingChapter

7 Citations (Scopus)

Abstract

Genetic Algorithm (GA) is one of the most well-regarded evolutionary algorithms in the history. This algorithm mimics Darwinian theory of survival of the fittest in nature. This chapter presents the most fundamental concepts, operators, and mathematical models of this algorithm. The most popular improvements in the main component of this algorithm (selection, crossover, and mutation) are given too. The chapter also investigates the application of this technique in the field of image processing. In fact, the GA algorithm is employed to reconstruct a binary image from a completely random image.

Original languageEnglish
Title of host publicationStudies in Computational Intelligence
PublisherSpringer Verlag
Pages69-85
Number of pages17
DOIs
Publication statusPublished - 1 Jan 2020
Externally publishedYes

Publication series

NameStudies in Computational Intelligence
Volume811
ISSN (Print)1860-949X

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Cite this

Mirjalili, S., Song Dong, J., Sadiq, A. S., & Faris, H. (2020). Genetic algorithm: Theory, literature review, and application in image reconstruction. In Studies in Computational Intelligence (pp. 69-85). (Studies in Computational Intelligence; Vol. 811). Springer Verlag. https://doi.org/10.1007/978-3-030-12127-3_5