A new genetic algorithm technique uses multiple parents for smoother, faster optimization.

Researchers have developed a new method for genetic algorithms that combines traits from multiple 'parent' solutions, not just two. Using a mathematically structured weighting system based on Pascal's triangle, it creates offspring that inherit more stable, central characteristics. This reduces disruptive variance during the search process. In tests on problems like circuit design and route optimization, it achieved performance gains of 9-22% over standard methods, with smoother and more reliable convergence.