RETRACTED ARTICLE: Discrete optimization method based on grassmannian parameterization in multidimensional dichotomic data structuring

A solution of the large computational time problem arising in multidimensional data structuring is addressed by employing algebraic properties of finite geometries. A vector parameterization of the Grassmannian Gr₂(k, n) is proposed which makes it possible to minimize the amount of memory and reduce the number of operations required to solve the problem. An algorithm based on this parameterization and the Gray codes is constructed; the algorithm is suitable for parallel computation, which further reduces computation time.