Hybrid metaheuristic algorithms: a recent comprehensive review with bibliometric analysis

Abstract

Metaheuristic algorithms are widely used in various applications. Collaborating two or more algorithms in a hybrid form has shown great improvements in terms of the algorithm's performance. This paper highlights the recently published work during the last decade from a quantitative perspective. The biometric measures include the number of publications, citations, average citations per publication, h-index, and field-weighted citation impact (FWCI) based on the data extracted from the Scopus database. Statistical measures, co-occurrence and co-authorship maps, and illustrative graphs have been implemented using software tools. According to the collected data, about 3469 articles have been published during the last decade with an increasing rate of 44.1 papers per year. Most of these articles have been published as journal articles with a percentage of 68.3%, followed by conference articles occupied 29.5%. China, India and Iran contributed the largest number of articles at 1076, 965, and 239, respectively. Parouha, Verma, and Kamel, are the top-ranked authors with 14, 10, and 9 publications, respectively. The most areas of interest are computer science, engineering and mathematics with publication percentages of 27.69%, 25.55% and 13.91%, respectively. The data presented in this paper gives the researchers a clear image of this hot topic to start new research.