This document summarizes a proposed novel method for crossover operators in genetic algorithms called the sigmoid crossover. It begins by discussing issues with existing crossover operators that use a fixed crossover probability, such as populations converging too quickly and getting stuck in local optima. It then proposes using a sigmoid probability distribution for crossover instead of a fixed value. This distribution is based on the genetic distance between chromosomes, with chromosomes that are more different having a higher chance of crossover. The document provides mathematical background on sigmoid functions and genetic distance. It then describes the proposed sigmoid crossover method and how it modifies the typical genetic algorithm crossover procedure by replacing the fixed probability with one based on genetic distance. This is intended to help preserve genetic diversity in the population and give a