In this paper, we propose an algorithm based on so-called ruin and recreate (R&R) principle. The R&R approach is conceptual simple but at the same time powerful meta-heuristic for combinatorial optimization problems. The main components of this method are a ruin (mutation) procedure and a recreate (improvement) procedure. We have applied the R&R principle based algorithm for a well-known combinatorial optimization problem, the quadratic assignment problem (QAP). We tested this algorithm on a number of instances from the library of the QAP instances — QAPLIB. The results obtained from the experiments show that the proposed approach appears to be significantly superior to a “pure” tabu search on real-life and real-life like QAP instances.