Soft Computing Technique towards the Geometry Optimization of Atomic Clusters
Ranita Pal, Bhrigu Chakraborty, Pratim Kumar Chattaraj · 2024
The pursuit of global optimization is a significant area of interest for chemists, and soft computing (SC) techniques have proven helpful in mitigating the challenges associated with nonlinearity and instability and in improving the technological capabilities that come along with it. This chapter aims to explore the subject and shed light on the fundamental models of the most effective and widely used SC techniques for discovering the global minimum (GM) energy structures of various chemical systems. Here we discuss the application of various SC techniques, including neural networks, Particle Swarm Optimization, Artificial Bee Colony, Bonobo Optimizer, Firefly Algorithm, and some hybrid approaches, in the global optimization of chemical systems. This chapter also covers several works done by our group on the global optimization of various chemical systems, highlighting the integration of two hybrid techniques, which lead to superior results.