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

Faisal Alkhateeb, Ra'ed M. Al-Khatib, Iyad Abu Doush

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Artificial 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.

Original languageEnglish
Pages (from-to)354-370
Number of pages17
JournalInternational Journal of Computer Applications in Technology
Volume63
Issue number4
DOIs
StatePublished - 2020

Keywords

  • Applications
  • Artificial intelligence
  • Immune algorithm
  • Nature-inspired metaheuristics
  • Optimisations
  • Variants of immune algorithm

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