Finding Molecules with Specific Properties: Simulated Annealing vs. Evolution

TL;DR

This paper compares simulated annealing and evolutionary algorithms in optimizing molecules for high hyperpolarizability, demonstrating their comparable effectiveness in molecular design tasks.

Contribution

It provides a direct comparison of simulated annealing and evolutionary algorithms for molecular property optimization using SMILES representations.

Findings

Both methods are similarly effective in finding molecules with high hyperpolarizability.

The approaches are suitable for complex, realistic molecular design problems.

SMILES-based optimization is feasible with both algorithms.

Abstract

We compare the ability of a simulated annealing program and an evolutionary algorithm to find molecules with large molecular average hyperpolarizabilities. This property is an important component of nonlinear optical materials. Both optimization programs represent molecules as SMILES strings, a method that is widely used by chemists to describe molecular structure using short ASCII strings. Our results suggest that both approaches are comparable and can be used to solve a variety of more realistic problems of interest to chemists and material scientists.