Metaheuristic research: a comprehensive survey - Hussain, Kashif; Mohd Salleh, Mohd Najib; Shi, Cheng; Yuhui, Shi (Springer Nature, 2018)
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.