A survey for recent applications and variants of nature-inspired immune search algorithm

dc.contributor.authorAbou Doush, Iyad
dc.contributor.authorAlkhateeb, Faisal
dc.contributor.authorAl-Khatib, Ra'ed
dc.date.accessioned2021-12-22T08:28:06Z
dc.date.available2021-12-22T08:28:06Z
dc.date.issued2020-10-07
dc.description.abstractArtificial Immune Systems (AIS) is a well-known nature inspired and population based algorithm that proved its effectiveness for solving engineering and practical real-world problems. AIS can adapt to learning, has many models for different immune systems, which can be used to tackle different kinds of optimisation problems, and it can also be hybridised with other algorithms. In this paper, we extensively summarise the recent researches of AIS and categorise them based on the application problem to understand the current trend of the usage of this algorithm. In addition, we provide the up to date open research problems that are not solved by immune search algorithm, and they were solved recently by other algorithms. This can help in paving the road for future research directions in the AIS field.
dc.identifier.citationFaisal Alkhateeb, Ra'ed M. Al-Khatib , and Iyad Abu Doush (2020). Applications and variants of nature-inspired immune search algorithm: a survey. International Journal of Computer Applications in Technology 63 (4), 354-370. https://www.inderscience.com/info/inarticle.php?artid=110417
dc.identifier.urihttps://dspace.auk.edu.kw/handle/11675/8252
dc.identifier.urlhttps://www.inderscience.com/info/inarticle.php?artid=110417
dc.publisherInternational Journal of Computer Applications in Technology
dc.relation.otherCollege of Engineering and Applied Sciences
dc.titleA survey for recent applications and variants of nature-inspired immune search algorithm
dc.typeJournal Article
dc.typePeer-Reviewed
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