Crossover XOR

Crossover XOR is a process used in genetic algorithms to combine information from two parent solutions, aiming to produce improved offspring. It involves taking parts of each parent's data and merging them, often using the XOR (exclusive OR) operation, which compares bits and outputs 1 only when the bits differ. This method helps generate diverse new solutions by emphasizing differences, fostering exploration of possible options. Essentially, crossover XOR strategically combines characteristics of two solutions to create new candidates that may perform better in solving complex problems.