Shorman S.M.Sakinah Ali Pitchay2024-05-292024-05-292015181966082-s2.0-84923033670https://www.scopus.com/inward/record.uri?eid=2-s2.0-84923033670&partnerID=40&md5=57a91dca1b917511bfaed77d07ffed16https://oarep.usim.edu.my/handle/123456789/9567Indexed by SCOPUSThe Genetic Algorithm (GA) is becoming very attractive and suitable for solving problems where high computational performance is required. This paper describes theoretical aspects of genetic algorithms which are parameters used to get a result such as crossover, mutation, selection and fitness. Likewise, GA performs efficient search spaces to get an optimal solution. This paper also highlights several issues in which GA as a tool for recovering the image in variety domain. Generally, however this approach has some limitations, strengths and challenges that are also discussed in this paper. Findings on a simple simulation of GA are also presented. 2006-2015 Asian Research Publishing Network (ARPN).en-USEvolutionary algorithmsGenetic algorithmImage recoveryLimitationsStrengthstext::journal::journal article585593102