SBX

SBX (Simulated Binary Crossover) is an algorithm used in genetic and evolutionary computing to generate new candidate solutions by combining two existing ones. It mimics natural genetic crossover, but in a way that explores a wider range of possibilities around the parent solutions, improving search effectiveness. Think of it as blending attributes from two "parents" to create a "child" solution that inherits characteristics, helping optimize complex problems efficiently. SBX balances exploration and exploitation, making it useful in solving nonlinear, multi-dimensional problems where traditional methods may struggle.