A Parallel Matrix-Based Approach for Computing Approximations in Dominance-Based Rough Sets Approach

摘要

Dominance-based Rough Sets Approach (DRSA) is a useful tool for multi-criteria classification problems solving. Parallel computing is an efficient way to accelerate problems solving. Computation of approximations is a vital step to find the solutions with rough sets methodologies. In this paper, we propose a matrix-based approach for computing approximations in DRSA and design the corresponding parallel algorithms on Graphics Processing Unit (GPU). A numerical example is employed to illustrate the feasibility of the matrix-based approach. Experimental evaluations show the performance of the parallel algorithm.