An Enhanced Evaporation Rate Water-Cycle Algorithm for Global Optimization

Water-cycle algorithm based on evaporation rate (ErWCA) is a powerful enhanced version of the water-cycle (WCA) metaheuristics algorithm. ErWCA, like other algorithms, may still fall in sub-optimal region and have slow convergence, especially high-dimensional tasks problems. This paper suggests an ErWCA (EErWCA) version, which embeds local escaping operator (LEO) as internal updating process. also uses control-randomization operator. To verify this comparison between EErWCA namely, classical water cycle (WCA), butterfly optimization (BOA), bird swarm (BSA), crow search (CSA), grasshopper (GOA), Harris Hawks Optimization (HHO), whale (WOA), dandelion optimizer (DO) fire hawks (FHO) using IEEE CEC 2017, was performed. The experimental analytical results show adequate performance proposed