Nature Inspired Algorithm
Nature-inspired algorithms (NIAs) draw inspiration from natural processes to solve complex optimization problems across diverse fields. Current research emphasizes developing and refining specific NIAs, such as ant colony optimization, shrike optimization, and moth flame optimization, often comparing their performance against established methods and exploring their application in areas like urban planning, software engineering, and biomedical image processing. This research is significant because NIAs offer efficient and robust solutions to computationally challenging problems, impacting fields ranging from engineering design to healthcare and machine learning. Furthermore, a growing focus on the environmental impact of algorithms is driving the exploration of more energy-efficient NIA designs.