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

被引：8
|
作者：
Alkhateeb F. [1 ]
Al-Khatib R.M. [1 ]
Doush I.A. [1 ,2 ]
机构：
[1] Computer Science Department, Yarmouk University, Irbid
[2] Computing Department, American University of Kuwait, Salmiya
来源：
International Journal of Computer Applications in Technology | 2020年 / 63卷 / 04期
关键词：
Applications; Artificial intelligence; Immune algorithm; Nature-inspired metaheuristics; Optimisations; Variants of immune algorithm;
D O I：
10.1504/IJCAT.2020.110417
中图分类号：
学科分类号：
摘要：
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. © 2020 Inderscience Enterprises Ltd.
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页码：354 / 370
页数：16
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