Research Area:  Metaheuristic Computing

Abstract:

This study presents an extensive analysis of ten emerging swarm intelligence metaheuristic techniques, namely Emperor Penguins Colony (EPC), Harris Hawks Optimizer (HHO), Butterfly Optimization Algorithm (BOA), Spotted Hyena Optimizer (SHO), Crow search algorithm (CSA), Whale optimization algorithm (WOA), Red Deer Algorithm (RDA), Ant Lion Optimizer (ALO), Dragonfly Algorithm (DA) and Grey wolf optimization (GWO). Here, a Quad–fold review strategy comprised of planning, shortlisting, extraction, and execution have been adhered to compile this meta-analysis. The mathematical models and working principles of these techniques have been briefly elucidated. The variants of these meta-heuristic techniques have also been explored and presented. The research trend of these metaheuristic methods has also been highlighted. The findings indicate that these methods are widely used to solve different problems viz: image segmentation, optimal power flow, air pollution forecasting, drug design, wireless sensor networks, disease diagnosis, transport, and routing. Furthermore, in the healthcare sector, the use of SI techniques in selecting optimal features for diagnosis of different diseases like Cancer, Alzheimer-s, Kidney disease, Anemia, Viral infection, Skin diseases have also been highlighted. Moreover, it is observed that the education-related optimization problems have been deeply explored by these meta-heuristic techniques whereas, weather forecasting is recognized as the least explored area. The binary, chaotic, and hybrid variants of EPC, HHO, BOA, SHO, CSA, WOA RDA, ALO, DA, and GWO of these metaheuristics techniques need to be deeply explored in healthcare for skin diseases, ophthalmology, viral infection, allergy along with distinct mental disorders. Finally, for better performance, the exploitation and exploration phases of these methods need to be carefully balanced.

Keywords:  
Swarm intelligence
Feature selection
Healthcare
Meta-heuristics
Research trend

Author(s) Name:  Preeti Monga, Manik Sharma, Sanjeev Kumar Sharma

Publisher name:  Elsevier

DOI:  10.1016/j.jksuci.2021.11.016

Volume Information:  Volume 34, Issue 10, Part B, November 2022, Pages 9622-9643

Paper Link:   https://www.sciencedirect.com/science/article/pii/S131915782100330X