| Title | Metaheuristic research: a comprehensive survey |
| Author | |
| Corresponding Author | Salleh, Mohd Najib Mohd |
| Publication Years | 2019-12
|
| DOI | |
| Source Title | |
| ISSN | 0269-2821
|
| EISSN | 1573-7462
|
| Volume | 52Issue:4Pages:2191-2233 |
| Abstract | Because of successful implementations and high intensity, metaheuristic research has been extensively reported in literature, which covers algorithms, applications, comparisons, and analysis. Though, little has been evidenced on insightful analysis of metaheuristic performance issues, and it is still a "black box" that why certain metaheuristics perform better on specific optimization problems and not as good on others. The performance related analyses performed on algorithms are mostly quantitative 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 real data from 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 (33 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 research gaps and future directions. The objective is to highlight potential open questions and critical issues raised in literature. The work provides guidance for future research to be conducted more meaningfully that can serve for the good of this area of research. |
| Keywords | |
| URL | [Source Record] |
| Indexed By | |
| Language | English
|
| Important Publications | ESI Highly Cited Papers
|
| SUSTech Authorship | Others
|
| Funding Project | National Natural Science Foundation of China[61672334]
; National Natural Science Foundation of China[61773119]
; National Natural Science Foundation of China[61771297]
|
| WOS Research Area | Computer Science
|
| WOS Subject | Computer Science, Artificial Intelligence
|
| WOS Accession No | WOS:000491051000002
|
| Publisher | |
| EI Accession Number | 20180604756938
|
| EI Keywords | Benchmarking
; Evolutionary algorithms
; Global optimization
; Optimization
; Surveys
; Swarm intelligence
|
| ESI Classification Code | Engineering Research:901.3
; Optimization Techniques:921.5
|
| ESI Research Field | COMPUTER SCIENCE
|
| Data Source | Web of Science
|
| Citation statistics |
Cited Times [WOS]:353
|
| Document Type | Journal Article |
| Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/42124 |
| Department | Department of Computer Science and Engineering |
| Affiliation | 1.Univ Tun Hussein Onn Malaysia, Fac Comp Sci & Informat Technol, Johor Baharu, Malaysia 2.Shaanxi Normal Univ, Sch Comp Sci, Xian, Shaanxi, Peoples R China 3.Southern Univ Sci & Technol, Dept Comp Sci & Engn, Shenzhen, Peoples R China |
| Recommended Citation GB/T 7714 |
Hussain, Kashif,Salleh, Mohd Najib Mohd,Cheng, Shi,et al. Metaheuristic research: a comprehensive survey[J]. ARTIFICIAL INTELLIGENCE REVIEW,2019,52(4):2191-2233.
|
| APA |
Hussain, Kashif,Salleh, Mohd Najib Mohd,Cheng, Shi,&Shi, Yuhui.(2019).Metaheuristic research: a comprehensive survey.ARTIFICIAL INTELLIGENCE REVIEW,52(4),2191-2233.
|
| MLA |
Hussain, Kashif,et al."Metaheuristic research: a comprehensive survey".ARTIFICIAL INTELLIGENCE REVIEW 52.4(2019):2191-2233.
|
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| Hussain-2019-Metaheu（1303KB） | Restricted Access | -- | ||||
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