Global Optimization: A Soft Computing Perspective

Tackling the problem of global optimization is one of the most important domains that physicists and chemists are working on. The use of soft computing (SC) techniques has made this easier by reducing nonlinearity and instability and making it technologically rich. This Perspective aims at explaining the basic mathematical models of the most efficient and commonly used SC techniques in computational chemistry for finding the global minimum (GM) energy structures of chemical systems. In this Perspective, we discuss the global optimizations of several chemical systems that our group has worked on using CNN, PSO, FA, ABC, BO, and some hybrid techniques, two of which are interfaced to achieve better-quality results.

Automated summary

Tackling the problem of global optimization is important in the fields of physics and chemistry. Soft computing techniques have made this process easier by reducing nonlinearity and instability. This Perspective discusses the mathematical models and applications of efficient soft computing techniques in computational chemistry for finding the global minimum energy structures of chemical systems. The authors present examples of global optimizations of various chemical systems using CNN, PSO, FA, ABC, BO, and hybrid techniques.