Solving Full NxNxN Rubik’s Supercube Using Genetic Algorithm

Abstract This article presents an algorithm using an evolutionary approach to the problem of solving a full Rubik's NxNxN supercube i.e. orienting all cubies, including internal ones, not only by their face colors, but to the same orientation in 3D space. The problem is formally defined by a matrix representation using affine transformations of cubies. The solving strategy consists of series of genetic algorithms which try to find better cube configuration from the current one. After finding one, moves are executed, changing current configuration. This strategy is repeated until solving the cube. Genetic algorithm restricts movements to the current cluster, solving the cube in stages from the center of the cube to the outside. Movements which solve clusters are saved in the form of macros and used for training and acceleration of the algorithm. The goal of the algorithm is to minimize solving time, not the count of moves.