Performance Analysis of Some New Hybrid Metaheuristic Algorithms for High‐Dimensional Optimization Problems
Souvik Ganguli, Gagandeep Kaur, Prasanta Sarkar · 2021
The chapter tests the performance of five global metaheuristic algorithms based on firefly optimization technique to obtain the solution of some high-dimensional benchmark problems without constraints. Firefly algorithm (FA) has been profitably compounded with several famous metaheuristic algorithms to present these excellent performing computation algorithms. The chapter discusses the limitations of the proposed topologies and provides some directions of research ahead with the help of hybrid firefly techniques. Three types of test functions, namely unimodal, multi-modal and fixed dimensional multi-modal functions were taken up to justify both the exploration and exploitation features of these global optimization techniques. The results determined were compared with about eighteen algorithms from the literature. The hybrid techniques proved superior in comparison to the individual methods. A common non-parametric test, namely Wilcoxon test with the inclusion of Holm-Bonferroni corrections, further confirms the validity of the results obtained.