Metaheuristic research: a comprehensive survey

Hussain, Kashif and Mohd Salleh, Mohd Najib and Shi, Cheng and Yuhui, Shi (2018) Metaheuristic research: a comprehensive survey. Artificial Intelligence Review, 52. pp. 2191-2233. ISSN 0269-2821

[img] Text
AJ 2018 (122).pdf
Restricted to Registered users only

Download (2MB) | Request a copy


Because of successful implementations and high intensity of research, metaheuristic research has been extensively reported in literature, which covers algorithms, applications, comparisons, and analysis. Though, it has been evidenced that little has been done on insightful analysis of metaheuristic performance issues, and it is still a “black box” why certain metaheuristics perform better on specific optimization problems and not as good on others. The performance related analysis, which have been performed on specific algorithms, are mostly qualitative via performance validation metrics like mean error, standard deviation, and co-relations have been used. Moreover, the performance tests are often performed on specific benchmark functions - few studies are those which involve data from real-life scientific or engineering optimization problems. In order to draw a comprehensive picture of metaheuristic research, this paper performs a survey of metaheuristic research in literature which consists of 1222 publications from year 1983 to 2016 (thirty three years). Based on the collected evidence, this paper addresses four dimensions of metaheuristic research: introduction of new algorithms, modifications and hybrids, comparisons and analysis, and future directions. The main objective is to highlight potential open questions and critical issues raised in literature. This will guide future researchers to conduct more meaningful research that can serve for the good of this area of research.

Item Type: Article
Uncontrolled Keywords: Metaheuristic; optimization; global optimization; swarm intelligence; evolutionary algorithms
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA76 Computer software
T Technology > T Technology (General)
Divisions: Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User: UiTM Student Praktikal
Date Deposited: 21 Dec 2021 07:16
Last Modified: 21 Dec 2021 07:16

Actions (login required)

View Item View Item